EP3427653A1 - Biological information analysis device and system, and program - Google Patents

Biological information analysis device and system, and program Download PDF

Info

Publication number
EP3427653A1
EP3427653A1 EP17782515.5A EP17782515A EP3427653A1 EP 3427653 A1 EP3427653 A1 EP 3427653A1 EP 17782515 A EP17782515 A EP 17782515A EP 3427653 A1 EP3427653 A1 EP 3427653A1
Authority
EP
European Patent Office
Prior art keywords
blood pressure
breathing
time
biological information
information analysis
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
EP17782515.5A
Other languages
German (de)
French (fr)
Other versions
EP3427653B1 (en
EP3427653A4 (en
Inventor
Hiroshi Nakajima
Hirotaka Wada
Naoki Tsuchiya
Masaaki Kasai
Eriko Kan
Toru Uenoyama
Keiichi Obayashi
Ayako Kokubo
Yuya Ota
Toshikazu Shiga
Mitsuo Kuwabara
Hironori Sato
Ken Miyagawa
Masakazu Tsutsumi
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Omron Corp
Omron Healthcare Co Ltd
Original Assignee
Omron Corp
Omron Healthcare Co Ltd
Omron Tateisi Electronics Co
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Omron Corp, Omron Healthcare Co Ltd, Omron Tateisi Electronics Co filed Critical Omron Corp
Publication of EP3427653A1 publication Critical patent/EP3427653A1/en
Publication of EP3427653A4 publication Critical patent/EP3427653A4/en
Application granted granted Critical
Publication of EP3427653B1 publication Critical patent/EP3427653B1/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/026Measuring blood flow
    • A61B5/029Measuring or recording blood output from the heart, e.g. minute volume
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • A61B5/02108Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/02028Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A61B5/02055Simultaneously evaluating both cardiovascular condition and temperature
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • A61B5/02108Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • A61B5/02116Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics of pulse wave amplitude
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • A61B5/02108Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • A61B5/02125Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics of pulse wave propagation time
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • A61B5/022Measuring pressure in heart or blood vessels by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • A61B5/022Measuring pressure in heart or blood vessels by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers
    • A61B5/02225Measuring pressure in heart or blood vessels by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers using the oscillometric method
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • A61B5/022Measuring pressure in heart or blood vessels by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers
    • A61B5/02233Occluders specially adapted therefor
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024Detecting, measuring or recording pulse rate or heart rate
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02438Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/08Detecting, measuring or recording devices for evaluating the respiratory organs
    • A61B5/0816Measuring devices for examining respiratory frequency
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1118Determining activity level
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • A61B5/318Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346Analysis of electrocardiograms
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • A61B5/318Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346Analysis of electrocardiograms
    • A61B5/349Detecting specific parameters of the electrocardiograph cycle
    • A61B5/352Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4836Diagnosis combined with treatment in closed-loop systems or methods
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4884Other medical applications inducing physiological or psychological stress, e.g. applications for stress testing
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802Sensor mounted on worn items
    • A61B5/681Wristwatch-type devices
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813Specially adapted to be attached to a specific body part
    • A61B5/6824Arm or wrist
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A61B5/7207Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts
    • A61B5/721Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7221Determining signal validity, reliability or quality
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7239Details of waveform analysis using differentiation including higher order derivatives
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271Specific aspects of physiological measurement analysis
    • A61B5/7278Artificial waveform generation or derivation, e.g. synthesising signals from measured signals
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271Specific aspects of physiological measurement analysis
    • A61B5/7282Event detection, e.g. detecting unique waveforms indicative of a medical condition
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/74Details of notification to user or communication with user or patient ; user input means
    • A61B5/742Details of notification to user or communication with user or patient ; user input means using visual displays
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/74Details of notification to user or communication with user or patient ; user input means
    • A61B5/742Details of notification to user or communication with user or patient ; user input means using visual displays
    • A61B5/743Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/74Details of notification to user or communication with user or patient ; user input means
    • A61B5/746Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61FFILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
    • A61F5/00Orthopaedic methods or devices for non-surgical treatment of bones or joints; Nursing devices; Anti-rape devices
    • A61F5/56Devices for preventing snoring
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M16/00Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes
    • A61M16/021Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes operated by electrical means
    • A61M16/022Control means therefor
    • A61M16/024Control means therefor including calculation means, e.g. using a processor
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/16Constructional details or arrangements
    • G06F1/1613Constructional details or arrangements for portable computers
    • G06F1/163Wearable computers, e.g. on a belt
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2560/00Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
    • A61B2560/02Operational features
    • A61B2560/0242Operational features adapted to measure environmental factors, e.g. temperature, pollution
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02Details of sensors specially adapted for in-vivo measurements
    • A61B2562/029Humidity sensors
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • A61B5/02141Details of apparatus construction, e.g. pump units or housings therefor, cuff pressurising systems, arrangements of fluid conduits or circuits
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/026Measuring blood flow
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/08Detecting, measuring or recording devices for evaluating the respiratory organs
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14532Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14542Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring blood gases
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4806Sleep evaluation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4806Sleep evaluation
    • A61B5/4818Sleep apnoea
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/683Means for maintaining contact with the body
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • A61B5/7257Details of waveform analysis characterised by using transforms using Fourier transforms
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271Specific aspects of physiological measurement analysis
    • A61B5/7275Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M2021/0005Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
    • A61M2021/0022Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus by the tactile sense, e.g. vibrations
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M2021/0005Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
    • A61M2021/0027Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus by the hearing sense
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M2021/0005Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
    • A61M2021/0044Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus by the sight sense
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M21/00Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
    • A61M2021/0005Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
    • A61M2021/0083Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus especially for waking up

Definitions

  • the present invention relates to technology for acquiring useful information from a blood pressure waveform that has been measured.
  • Patent Document 1 JP 2008-61824A discloses that a blood pressure waveform is measured using a tonometry method, and pieces of information such as an AI (Augmentation Index) value, a pulse wave period, a baseline fluctuation rate, sharpness, and an ET (Ejection Time) are acquired from the blood pressure waveform.
  • AI Algmentation Index
  • ET Ejection Time
  • Patent Document 2 JP 2005-532111A discloses that a blood pressure waveform is measured using a wristwatch-type blood pressure meter, in which a mean arterial pressure, a mean systolic pressure, a mean diastolic pressure, a mean systolic pressure indicator, and a mean diastolic pressure indicator are calculated from the blood pressure waveform, and an alert is output when any of these values deviates from a reference value.
  • blood pressure can be controlled by using a breathing technique.
  • the amount of change in blood pressure varies for each person due to the influence of the characteristics and the disease state of each person, even if the same breathing pattern is used. Therefore, a standard routine for improvement in breathing does not have a sufficient blood pressure control effect.
  • a user experiences an increase in blood pressure or poor physical condition even if the user knows that blood pressure can be controlled by using a breathing technique, the user does not know what specific measures can be taken.
  • the inventors of the present invention have worked hard to develop a blood pressure measurement device that can accurately measure an ambulatory blood pressure waveform for each heartbeat, and to put such a device into practical use. Through experiments performed on subjects during the development phase, the inventors have found that it can be possible to quantitatively evaluate a relationship between breathing and changes in blood pressure by accurately and non-invasively monitoring ambulatory blood pressure waveforms for each heartbeat.
  • the present invention aims to provide a novel technology for acquiring information regarding a relationship between breathing and changes in blood pressure.
  • the present invention employs the following configurations.
  • a biological information analysis device is a biological information analysis device that includes: an indicator extraction unit configured to extract, from time-series data regarding blood pressure waveforms consecutively measured by a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat, and from time-series data regarding breathing measured by a respiration sensor during a period of time corresponding to the time-series data regarding blood pressure waveforms, an indicator indicating a relationship between the user's breathing and changes in blood pressure; and a processing unit configured to perform processing that is based on the indicator thus extracted.
  • analysis is performed using time-series data regarding blood pressure waveforms measured from each heartbeat of the user, and time-series data regarding breathing measured during a period corresponding thereto. Therefore, it is possible to quantitatively analyze a relationship (a cause-effect relationship or a correlation) between breathing and change in blood pressure, which is a characteristic that is unique to the user.
  • the indicator extraction unit is configured to specify a plurality of periods of time that have the same breathing pattern, from the time-series data regarding breathing, and extract an indicator indicating the relationship between breathing and changes in blood pressure for the breathing pattern, from pieces of data regarding blood pressure waveforms respectively corresponding to the plurality of periods of time.
  • the indicator extraction unit is configured to extract, as the indicator, a trend in changes in blood pressure and/or the amount of changes that is/are common to pieces of data regarding blood pressure waveforms.
  • the indicator extraction unit is configured to classify ways the user breathes, into a plurality of breathing patterns, based on the time-series data regarding the user's breathing. By classifying the user's breathing into a plurality of breathing patterns based on time-series data regarding the user's breathing, it is possible to acquire breathing patterns that are suitable for the user's characteristics.
  • the time-series data regarding breathing includes, for each of a plurality of periods of time that include an exhalation period and an inhalation period, the length of the period of time and/or the amount of breath.
  • the indicator extraction unit is configured to classify the plurality of periods of time into a plurality of breathing patterns based on the length of the period of time and/or the amount of breath. This is because the influence on blood pressure varies depending on the length of time spent for exhaling and inhaling and the amount of breath that is exhaled and inhaled.
  • the indicator extraction unit is configured to extract an indicator indicating the relationship between breathing and changes in blood pressure for each of the plurality of breathing patterns. By identifying the relationship between breathing and changes in blood pressure for each of the plurality of breathing patterns, it is possible to acquire information that is very useful for knowing characteristics of the user's respiratory and circulatory organs.
  • the processing unit is configured to perform processing to output information representing the relationship between the user's breathing and changes in blood pressure, based on the indicator. Because such information is provided, the user can understand the relationship between his/her breathing and changes in blood pressure, and recognize an effective way of breathing when regulating blood pressure.
  • the indicator extraction unit is configured to generate, for each of the plurality of breathing patterns, a relationship table that defines an indicator indicating the relationship between breathing and changes in blood pressure
  • the processing unit is configured to select a breathing pattern that is to be followed in order to achieve a desired change in blood pressure, based on the relationship table, and recommend the selected breathing pattern to the user.
  • the indicator extraction unit includes, as changes in blood pressure, at least one of: changes in systolic blood pressure; changes in diastolic blood pressure; changes in an AI (Augmentation Index); changes in the number of times a surge in blood pressure occurs; and changes in the amount of an increase in a surge in blood pressure.
  • changes in blood pressure at least one of: changes in systolic blood pressure; changes in diastolic blood pressure; changes in an AI (Augmentation Index); changes in the number of times a surge in blood pressure occurs; and changes in the amount of an increase in a surge in blood pressure.
  • the present invention can be interpreted as a biological information analysis device or system that is provided with at least one of the above-described configurations or at least one of the above-described functions.
  • the present invention can also be interpreted as a biological information analysis method that includes at least part of the above-described processing, or a program that causes a computer to execute such a method, or a computer-readable recording medium on which such a program is recorded in a non-transitory manner.
  • the present invention can be formed by combining the above-described configurations and the above-described kinds of processing with each other unless no technical inconsistency occurs.
  • FIG. 1 shows a schematic external configuration of a biological information analysis system 10 according to an embodiment of the present invention.
  • FIG. 1 shows a state in which the biological information analysis system 10 is worn on the left wrist.
  • the biological information analysis system 10 includes a main body 11 and a belt 12 that is fixed to the main body 11.
  • the biological information analysis system 10 is a so-called wearable device, and is worn such that the main body 11 is in contact with the skin on the palm side of the wrist, and the main body 11 is located over a radial artery TD that lies beneath the skin.
  • the device is configured to be worn on the radial artery TD in the present embodiment, the device may be configured to be worn on another superficial artery.
  • FIG. 2 is a block diagram showing a hardware configuration of the biological information analysis system 10.
  • the biological information analysis system 10 includes a measurement unit 2 and the biological information analysis device 1.
  • the measurement unit 2 is a device that performs measurement to acquire information that is used to analyze biological information, and includes a blood pressure measurement unit 20, a body movement measurement unit 21, an environment measurement unit 22, and a respiration measurement unit 28.
  • the configuration of the measurement unit 2 is not limited to that shown in FIG. 2 .
  • a unit that measures biological information other than blood pressure or a body movement e.g. body temperature, blood-sugar level, or brain waves
  • any unit that is not used in the example described below is not an essential component, and may be omitted from the biological information analysis system 10.
  • the biological information analysis device 1 is a device that analyzes biological information based on information acquired from the measurement unit 2, and includes a control unit 23, an input unit 24, an output unit 25, a communication unit 26, and a storage unit 27.
  • the units 20 to 27 are connected to each other so that signals can be exchanged between them via a local bus or other signal lines.
  • the biological information analysis system 10 also includes a power supply (a battery), which is not shown.
  • the blood pressure measurement unit 20 measures a pressure pulse wave from the radial artery TD by using a tonometry method.
  • the tonometry method is for forming a flat area in the artery TD by pressing the artery from the skin with appropriate pressure, adjusting the balance between the internal pressure and the external pressure of the artery, and non-invasively measuring the pressure pulse wave using a pressure sensor.
  • the body movement measurement unit 21 includes a tri-axis acceleration sensor, and measures the movement of the user's body (body movement) using this sensor.
  • the body movement measurement unit 21 may include a circuit that converts the format of an output from the tri-axis acceleration sensor into a format that is readable to the control unit 23.
  • the environment measurement unit 22 measures environmental information that may affect mental and physical conditions of the user (in particular the blood pressure).
  • the environment measurement unit 22 may include, for example, an atmospheric temperature sensor, a humidity sensor, an illuminance sensor, an altitude sensor, a position sensor, and so on.
  • the environment measurement unit 22 may include a circuit that converts the format of outputs from these sensors and so on into a format that is readable to the control unit 23.
  • the respiration measurement unit 28 is a unit that measures the state of the user's breathing.
  • the respiration measurement unit 28 may include, for example, a respiration sensor such as a flow sensor.
  • the respiration measurement unit 28 can at least discern between exhalation and inhalation, and measure the duration of exhalation and the duration of inhalation, and preferably, it can also measure the amount of breath.
  • the respiration measurement unit 28 may include a circuit that converts the format of outputs from the respiration sensor and so on into a format that is readable to the control unit 23.
  • the control unit 23 performs various kinds of processing, such as controlling each unit of the biological information analysis system 10, acquiring data from the measurement unit 2, storing the acquired data in the recording unit 27, processing and analyzing data, and inputting and outputting data.
  • the control unit 23 includes a hardware processor (hereinafter referred to as the "CPU") a ROM (Read Only Memory), a RAM (Random Access Memory), and so on. Processing that is performed by the control unit 23, which will be described later, is realized by the CPU reading and executing a program stored in the ROM or the storage unit 27.
  • the RAM functions as a work memory that is used by the control unit 23 when performing various kinds of processing.
  • Each of the constituent components of the embodiment such as a measurement unit, an indicator extraction unit, a processing unit, a determination unit, a risk database, an input unit, an output unit, a case database, and so on may be implemented as pieces of hardware in the biological information analysis system 10.
  • the indicator extraction unit, the processing unit, and the determination unit may receive an executable program stored in the storage unit 27, and execute the program.
  • the indicator extraction unit, the processing unit, and the determination unit may receive data from the blood pressure measurement unit 20, the body movement measurement unit 21, the environment measurement unit 22, the input unit 24, the output unit 25, the communication unit 26, the storage unit 27, and so on as required.
  • Databases such as the risk database and the case database may be implemented using the storage unit 27 and so on, and store pieces of information that are arranged such that a data search and data accumulation can be easily performed.
  • the configuration, operations, and so on of the biological information analysis system 10 are disclosed in JP 2016-082069A .
  • the contents of this disclosure are incorporated herein by reference.
  • the configuration, operations, and so on of the blood pressure measurement unit are disclosed in JP 2016-087003A .
  • the contents of this disclosure are incorporated herein by reference.
  • the input unit 24 provides an operation interface for the user.
  • an operation button for example, an operation button, a switch, a touch panel, and so on may be used.
  • the output unit 25 provides an interface that outputs information to the user.
  • a display device such as a liquid crystal display
  • an audio output device or a beeper that outputs information using audio
  • an LED that outputs information by blinking
  • a vibration device that outputs information by vibrating, and so on may be used.
  • the communication unit 26 performs data communication with another device. Any data communication method such as a wireless LAN or Bluetooth (registered trademark) may be used.
  • the storage unit 27 is a storage medium that can store data and from which data can be read out, and stores programs that are to be executed by the control unit 23, pieces of measurement data acquired from the measurement units, and various kinds of data acquired by processing the pieces of measurement data, and so on.
  • the storage unit 27 is a medium that accumulates pieces of information that are to be stored, through an electrical, magnetic, optical, mechanical, or chemical action. For example, a flash memory is used.
  • the storage unit 27 may be a portable unit such as a memory card, or built into the biological information analysis system 10.
  • At least one unit or all units out of the body movement measurement unit 21, environment measurement unit 22, the control unit 23, the input unit 24, the output unit 25, and the storage unit 27 may be configured as a device that is separate from the main body 11. That is, as long as the blood pressure measurement unit 20 and the main body 11 that incorporates a circuit that controls the blood pressure measurement unit 20 are configured to be wearable on a wrist, the configurations of other units can be freely designed. If this is the case, the main body 11 cooperates with another unit via the communication unit 26.
  • the functions of the control unit 23, the input unit 24, and the output unit 25 may be realized using a smartphone application, and required data may be acquired from an activity monitor that has the functions of the body movement measurement unit 21 and the environment measurement unit 22.
  • a sensor that measures biological information other than blood pressure may be provided. For example, a sleep sensor, a pulse oximeter (SpO2 sensor), a blood-sugar level sensor, and the like may be combined.
  • the sensor (the blood pressure measurement unit 20) that measures blood pressure and the component (including the control unit 23 and so on) that performs processing to analyze blood pressure waveform data
  • the component (including the control unit 23 and so on) that performs processing to analyze biological information
  • the device that includes the combination of the measurement unit and the biological information analysis device is referred to as a biological information analysis system.
  • these names are given for descriptive purposes, and the measurement unit and the component that performs processing to analyze biological information may be referred to as a biological information analysis device as a whole, or other names may be used.
  • FIG. 3 is a cross-sectional view schematically showing the configuration of the blood pressure measurement unit 20 and a state in which measurement is performed.
  • the blood pressure measurement unit 20 includes a pressure sensor 30 and a pressurizing mechanism 31 for pressing the pressure sensor 30 against a wrist.
  • the pressure sensor 30 includes a plurality of pressure detection elements 300.
  • the pressure detection elements 300 detect pressure and convert the pressure into an electrical signal.
  • elements that utilize a piezoresistive effect may be preferably used.
  • the pressurizing mechanism 31 includes, for example, an air bag and a pump that adjusts the internal pressure of the air bag. As a result of the control unit 23 controlling the pump to increase the internal pressure of the air bag, the air bag expands and the pressure sensor 30 is pressed against the surface of the skin.
  • the pressurizing mechanism 31 may be any mechanism as long as it can adjust the pressing force of the pressure sensor 30 applied to the surface of the skin, and is not limited to a mechanism that uses an air bag.
  • the control unit 23 controls the pressurizing mechanism 31 of the blood pressure measurement unit 20 to keep the pressing force of the pressure sensor 30 in an appropriate state (a tonometry state). Then, pressure signals detected by the pressure sensor 30 are sequentially acquired by the control unit 23. Pressure signals acquired from the pressure sensor 30 are generated by digitizing analogue physical amounts (e.g. voltage values) output by the pressure detection elements 300, through an A/D converter circuit or the like that employs a well-known technology. Preferable analogue values such as current values or resistance values may be employed as the analogue physical amounts, depending on the type of the pressure detection elements 300.
  • analogue physical amounts e.g. voltage values
  • Preferable analogue values such as current values or resistance values may be employed as the analogue physical amounts, depending on the type of the pressure detection elements 300.
  • Signal processing such as the aforementioned A/D conversion may be performed using a predetermined circuit provided in the blood pressure measurement unit 20, or performed by another unit (not shown) provided between the blood pressure measurement unit 20 and the control unit 23.
  • Each pressure signal acquired by the control unit 23 corresponds to an instantaneous value of the internal pressure of the radial artery TD. Therefore, it is possible to acquire time-series data regarding blood pressure waveforms by acquiring pressure signals with time granularity and continuity that make it possible to ascertain a blood pressure waveform for each heartbeat.
  • the control unit 23 stores the pressure signals sequentially acquired from the pressure sensor 30, in the storage unit 27, together with information regarding points in time at which the pressure signals were measured.
  • the control unit 23 may store the acquired pressure signals in the storage unit 27 without change, or store the pressure signals in the storage unit 27 after performing required signal processing on the pressure signals.
  • Required signal processing includes, for example, processing that is performed to calibrate each pressure signal such that the amplitude of the pressure signal matches the blood pressure value (e.g. the brachial blood pressure), processing that is performed to reduce or remove noise in each pressure signal, and so on.
  • FIG. 4 shows a blood pressure waveform measured by the blood pressure measurement unit 20.
  • the horizontal axis indicates time and the vertical axis indicates blood pressure.
  • the sampling frequency may be set to any value, it is preferably set to be no less than 100 Hz so that characteristics of the shape of a waveform corresponding to one heartbeat can be reproduced.
  • the period of one heartbeat is approximately one second, and therefore approximately one hundred or more data points can be acquired on a waveform corresponding to one heartbeat.
  • the blood pressure measurement unit 20 according to the present embodiment is advantageous in terms of the following.
  • the blood pressure measurement unit 20 can measure a blood pressure waveform for each heartbeat. As a result, it is possible to acquire various indicators related to blood pressure, the state of the heart, cardiovascular risks, and so on, based on the characteristics of the shape of the blood pressure waveform. In addition, it is possible to monitor for instantaneous values of blood pressure. Therefore, it is possible to instantaneously detect a blood pressure surge (a sudden rise in the blood pressure value), and to detect changes in blood pressure and irregularities in a blood pressure waveform that may occur in a very short period of time (corresponding to one to several heartbeats) without missing them.
  • a blood pressure surge a sudden rise in the blood pressure value
  • a blood pressure meter As a portable blood pressure meter, a blood pressure meter that is to be worn on a wrist or an upper arm and employs an oscillometric method to measure blood pressure has come into practical use.
  • a conventional portable blood pressure meter can only measure the mean value of blood pressure based on changes in the internal pressure of a cuff during a period of several seconds to a dozen or so seconds corresponding to a plurality of heartbeats, and cannot acquire time-series data regarding a blood pressure waveform for each heartbeat, unlike the blood pressure measurement unit 20 according to the present embodiment.
  • the blood pressure measurement unit 20 can record time-series data regarding blood pressure waveforms. By acquiring time-series data regarding blood pressure waveforms, and, for example, discerning characteristics of the blood pressure waveform related to temporal changes, or performing a frequency analysis on the time-series data to extract a specific frequency component, it is possible to acquire various indicators related to blood pressure, the state of the heart, cardiovascular risks, and so on.
  • the device employs a portable (wearable) type configuration, and less burden is placed on the user during measurement. Therefore, continuous measurement for a long time, and even 24-hour blood pressure monitoring, can be relatively easily performed. Also, since the device is of a portable type, changes in not only blood pressure under resting conditions, but also an ambulatory blood pressure (for example, during daily life or exercise) can be measured. As a result, it is possible to grasp how blood pressure is affected by behaviours in daily life (such as sleeping, eating, commuting, working, and taking medicine) and exercise, for example.
  • the blood pressure measurement unit 20 can be easily combined or linked with other sensors. For example, it is possible to make an evaluation of a cause-effect relationship or a composite evaluation with information that can be acquired by other sensors (e.g. a body movement, environmental information such as an atmospheric temperature, biological information such as SpO2 and respiration information).
  • other sensors e.g. a body movement, environmental information such as an atmospheric temperature, biological information such as SpO2 and respiration information.
  • FIG. 5 is a block diagram illustrating processing that is performed by the biological information analysis device 1.
  • the biological information analysis device 1 includes an indicator extraction unit 50 and a processing unit 51.
  • processing performed by the indicator extraction unit 50 and the processing unit 51 may be realized by the control unit 23 executing a program that is required for the processing.
  • the program may be stored in the storage unit 27.
  • the control unit 23 executes the required program, the subject program stored in the ROM or storage unit 27 is loaded to the RAM. Then, the control unit 23 interprets and executes the program loaded to the RAM, using the CPU, to control each constituent component.
  • At least one or all of the processing procedures executed by the indicator extraction unit 50 and the processing unit 51 may be realized using a circuit such as an ASIC or an FPGA.
  • at least one or all of the processing procedures executed by the indicator extraction unit 50 and the processing unit 51 may be realized using a computer (e.g. a smartphone, a tablet terminal, a personal computer, or a cloud server) that is separate from the main body 11.
  • the indicator extraction unit 50 acquires time-series data regarding blood pressure waveforms, which have been consecutively measured by the blood pressure measurement unit 20, from the storage unit 27.
  • the indicator extraction unit 50 extracts, from the acquired time-series data regarding blood pressure waveforms, indicators that are related to characteristics of the blood pressure waveforms.
  • characteristics of a blood pressure waveform include, for example, characteristics of the shape of a blood pressure waveform corresponding to one heartbeat, temporal changes in a blood pressure waveform, and frequency components of a blood pressure waveform.
  • characteristics of a blood pressure waveform are not limited to those listed above.
  • the extracted indicators are output to the processing unit 51.
  • characteristics and indicators regarding a blood pressure waveform there are various characteristics and indicators regarding a blood pressure waveform, and the characteristics and indicators that are to be extracted may be designed or selected as appropriate according to the purpose of processing that is to be performed by the processing unit 51. Characteristics and indicators that can be extracted from measurement data regarding blood pressure waveforms according to the present embodiment will be described later in detail.
  • the indicator extraction unit 50 may use measurement data that has been acquired by the body movement measurement unit 21 and/or measurement data that has been acquired by the environment measurement unit 22, in addition to measurement data regarding blood pressure waveforms. Also, although not shown in the drawings, pieces of measurement data that have been acquired by a sleep sensor, an SpO2 sensor, a blood-sugar level sensor, and the like may be combined with one another. By performing complex analysis on a plurality of kinds of measurement data acquired by a plurality of sensors, it is possible to perform more advanced information analysis of a blood pressure waveform.
  • a resting state and a moving state a state when an atmospheric temperature is high and a state when it is low
  • a light sleep state and a deep sleep state a breathing state and an apnea state
  • the processing unit 51 receives the indicators extracted by the indicator extraction unit 50.
  • the processing unit 51 performs processing that is based on the received indicators.
  • Various kinds of processing can be conceived of as processing that is based on the indicators.
  • the processing unit 51 may provide the values of the extracted indicators or changes in the values to a user, a doctor, a public health nurse, or the like to prompt the utilization of the indicators in the fields of health care, treatment, health guidance, and so on.
  • the processing unit 51 may estimate cardiovascular risks from the extracted indicators, or provide guidelines for health maintenance or risk mitigation.
  • the processing unit 51 may inform the user or his/her doctor, or perform control to prevent the user from performing an action that burdens his/her heart and so on, or to prevent a cardiovascular event from occurring.
  • FIG. 6 shows a waveform (a blood pressure waveform) of a pressure pulse wave from a radial artery corresponding to one heartbeat.
  • the horizontal axis indicates time t (msec) and the vertical axis indicates blood pressure BP (mmHg).
  • a blood pressure waveform is the waveform of a composite wave constituted by an "ejection wave” that is generated when the heart contracts and pumps out blood, and a “reflection wave” that is generated when an ejection wave is reflected at a branch point of a peripheral vessel or an artery.
  • the following shows examples of characteristic points that can be extracted from a blood pressure waveform corresponding to one heartbeat.
  • the indicator extraction unit 50 may use any algorithm to detect the above-described characteristic points.
  • the indicator extraction unit 50 may perform computations to obtain an nth order differential waveform of a blood pressure waveform, and detect the zero-crossing points to extract the characteristic points (the inflection points) of the blood pressure waveform (the points F1, F2, F4, F5, and F6 can be detected from the first order differential waveform, and the point F3 can be detected from the second order differential waveform or the fourth order differential waveform).
  • the indicator extraction unit 50 may read out, from the storage unit 27, a waveform pattern on which the characteristic points have been arranged in advance, and perform fitting of the waveform pattern to the target blood pressure waveform to specify the respective positions of the characteristic points.
  • the indicator extraction unit 50 performs computations based on time t and pressure BP of each of the above-described characteristic points F1 to F6, and can thus obtain various kinds of information (values, characteristic amounts, indicators, etc.) from the blood pressure waveform of one heartbeat.
  • information values, characteristic amounts, indicators, etc.
  • tx and BPx respectively represent time and blood pressure corresponding to a characteristic point Fx.
  • Basic statistics of these pieces of information can also be used as indicators.
  • Basic statistics include, for example, representative values (a mean value, a median value, a mode value, the maximum value, the minimum value, and so on) and the degree of scatter (dispersion, a standard deviation, a coefficient of variation, and so on).
  • Temporal changes in these pieces of information can also be used as indicators.
  • the indicator extraction unit 50 can also acquire an indicator called BRS (Baroreflex Sensitivity) by performing computations on pieces of heartbeat information.
  • BRS Baroreflex Sensitivity
  • This indicator indicates the ability to regulate blood pressure to be constant.
  • methods for calculating the indicator include a spontaneous sequence method. This is a method for only extracting a sequence in which the maximum blood pressure SBP and the pulse wave interval TA consecutively rise or fall over the period of three or more heartbeats in synchronization with each other, plotting the maximum blood pressure SBP and the pulse wave interval TA onto a two-dimensional plane, and defining the inclination of the regression line obtained through a least squares method as the BRS.
  • the use of the biological information analysis system 10 makes it is possible to acquire various kinds of information from blood pressure waveform data.
  • the biological information analysis system 10 need not implement all of the functions that are required to acquire all of the kinds of information described above.
  • the biological information analysis system 10 need only implement functions that are required to acquire necessary information, depending on the configuration of the biological information analysis system 10, who the user is, the purpose of use, the location of use, and so on.
  • each function may be provided as a program module (a piece of application software), and the biological information analysis system 10 may employ a mechanism with which a function can be added by installing a necessary program module on the biological information analysis system 10.
  • the present example proposes a method for suggesting a breathing technique that is suitable for the characteristics and the state of disease of each individual user in an objective manner by representing the relationship between breaths and changes in blood pressure based on time-series data regarding breathing and blood pressure measured from users.
  • the device according to the present example can accurately and non-invasively measure a blood pressure waveform for each heartbeat, and is thus able to quantitatively analyze the influence of each action of exhaling/inhaling on blood pressure or the waveform thereof.
  • the biological information analysis system 10 includes a respiration sensor that serves as the respiration measurement unit 28.
  • the biological information analysis system 10 may not be provided with a respiration measurement unit, and the biological information analysis system 10 may simply use data measured by another respiration sensor. If this is the case, measurement data regarding blood pressure waveforms and measurement data acquired by the respiration sensor can be associated with each other in terms of time, based on measurement time information (time stamps), for example.
  • a flow sensor that can detect the direction in which air flows, such as that disclosed in JP H10-185639A , can be favorably used.
  • This flow sensor detects an air flow caused by the breathing action to determine whether the action is exhalation or inhalation.
  • a pressure sensor or a vibration sensor may be used as a respiration sensor. If this is the case, body movement caused by the breathing action is detected by a pressure sensor, a vibration sensor, or the like that is attached to a body part, and thus the breathing action is indirectly detected.
  • FIG. 7 shows an example of a flowchart for processing according to the present example.
  • the user wears the biological information analysis system 10 and the respiration sensor, and blood pressure waveforms and breathing are measured (step 4500).
  • Time-series data regarding blood pressure waveforms and time-series data regarding breathing are stored in the storage unit 27.
  • the time-series data regarding breathing includes pieces of information regarding exhalation periods (periods of time during which air is exhaled) and pieces of information regarding inhalation periods (periods of time during which air is inhaled), which are arranged one after the other.
  • a piece of information regarding an exhalation period includes the start time and the end time of the period, the length of the period (also referred to as the duration of exhalation), and the amount of breath in the period (the amount of exhaled air, which is also referred to as an exhale amount).
  • a piece of information regarding an inhalation period includes the start time and the end time of the period, the length of the period (also referred to as the duration of inhalation), and the amount of breath in the period (the amount of inhaled air, which is also referred to as an inhale amount).
  • the indicator extraction unit 50 analyzes the relationship between breathing and changes in blood pressure (step 4501). Specifically, the indicator extraction unit 50 reads, from the storage unit 27, time-series data regarding blood pressure waveforms, and time-series data regarding breathing measured in the period corresponding to the time-series data regarding blood pressure waveforms. Thereafter, as shown in FIG. 8 , the indicator extraction unit 50 specifies exhalation periods and inhalation periods based on the time-series data regarding breathing, and divides the time-series data regarding blood pressure waveforms into blood pressure waveforms respectively corresponding to the periods. Thereafter, the indicator extraction unit 50 performs data mining processing such as cross tabulation or regression analysis on pieces of information regarding breathing respectively corresponding to the periods, and information regarding blood pressure waveforms corresponding thereto, to extract an indicator indicating the relationship between breathing and changes in blood pressure.
  • data mining processing such as cross tabulation or regression analysis
  • the indicator extraction unit 50 classifies (typifies) the ways the user breathes, into a plurality of patterns, based on information regarding breathing in each period.
  • the classification into breathing patterns may be performed based on, for example, the length of the period and/or the amount of breath.
  • exhalation periods and inhalation periods may be classified so as to be separate from each other, or classified into sets each consisting of an exhalation period and an inhalation period (each set is referred to as a breathing period).
  • the indicator extraction unit 50 may collect pieces of data regarding blood pressure waveforms for a plurality of periods that have the same breathing pattern, and extract, as indicators indicating the relationship between breathing and changes in blood pressure, a trend in changes in blood pressure (an increase, a decrease, no change, and so on) and/or the amount of changes (the amount of an increase, the amount of a decrease, and so on) that are/is common to the pieces of data regarding blood pressure waveforms.
  • a trend in changes in blood pressure an increase, a decrease, no change, and so on
  • the amount of changes the amount of an increase, the amount of a decrease, and so on
  • data regarding blood pressure waveforms corresponding to a given period may be “data regarding blood pressure waveforms in the given period” or “data regarding blood pressure waveforms of a plurality of periods that include the period and one or more periods that are previous and/or subsequent to the period”.
  • changes in blood pressure waveforms within one period are items that are to be used to evaluate changes in blood pressure.
  • changes in blood pressure waveforms within a plurality of periods are items that are to be used to evaluate changes in blood pressure.
  • SBP systolic blood pressure
  • DBP diastolic blood pressure
  • AI Algmentation Index
  • the amount of change in the number of times a surge in blood pressure has occurred is an item that is to be used to evaluate changes in blood pressure.
  • data regarding blood pressure waveforms corresponding to a given period “data regarding blood pressure waveforms measured upon a predetermined period of time elapsing after the period” may be used. Such an analysis is effective if the influence of breathing on blood pressure waveforms appears upon a predetermined period of time elapsing.
  • the indicator extraction unit 50 stores the relationship between breathing and changes in blood pressure (an indicator) acquired in step 4501 for each breathing pattern, in the storage unit 27, in the form of a relationship table (step 4502).
  • FIGS. 9A and 9B show an example of the relationship table. It can be seen from the relationship table shown in FIG. 9A that, if a small amount of air is inhaled in a short period of time, the SBP decreases by 10 mmHg, and if a large amount of air is inhaled even in a short period of time, the SBP decreases by 30 mmHg.
  • whether the duration of a period is long or short may be determined based on whether or not the duration of the period is longer than a threshold value.
  • the threshold value is stored in the storage unit 27, for example. Similarly, whether the amount of breath is large or small may be determined based on whether or not the amount of breath in the period is greater than a threshold value.
  • the threshold values may be fixed, or changed as appropriate according to the tendencies and the characteristics of the user. It can be seen from the relationship table shown in FIG. 9B that the SBP decreases by 4 mmHg per second during inhalation, and the SBP decreases by 10 mmHg per liter of breath. Note that tables shown in FIGS. 9A and 9B are examples, and it is also preferable that the amount of changes in the DBP and the amount changes in the AI are recorded. It can be said that these relationship tables are indicators indicating the relationship between breathing and change in blood pressure. The relationship tables thus generated are stored in the storage unit 27, and used for various kinds of processing that is performed by the processing unit 51.
  • the indicator extraction unit 50 may acquire, from the past case database, data of another subject who is similar to the user in terms of the relationship between breathing and changes in blood pressure, and generate a relationship table for the user, considering the data of the subject as well.
  • the indicator extraction unit 50 may acquire, from the past case database, data of another subject who is similar to the user in terms of the relationship between breathing and changes in blood pressure, and generate a relationship table for the user, considering the data of the subject as well.
  • the processing unit 51 may read a relationship table stored in the storage unit 27, and output information representing the relationship between the user's breathing and changes in blood pressure, from the output unit 25.
  • information representing the relationship between the user's breathing and changes in blood pressure may be output in the form of a table as shown in FIGS. 9A and 9B , or in a different form.
  • the processing unit 51 may perform breathing pattern recommendation processing based on a relationship table. Breathing pattern recommendation processing is performed to suggest a breathing pattern that is to be followed in order to achieve a desired change in blood pressure. For example, it is envisioned that a user experiences an increase in blood pressure or poor physical condition, and wishes to regulate blood pressure by using a breathing technique. If this is the case, the user inputs a target value of a change in blood pressure, using the input unit 24 of the biological information analysis system 10. For example, it is envisioned that that user has entered a target value to "lower the systolic blood pressure (SBP) by 30 mmHg".
  • SBP systolic blood pressure
  • the processing unit 51 refers to relationship tables in the storage unit 27, and designs a breathing pattern (the duration of exhalation, the duration of inhalation, an exhale amount, an inhale amount, the number of breaths, and so on) that is required to lower the SBP by 30 mmHg. At this time, if a plurality of kinds of breathing patterns can be conceived of, the most appropriate breathing pattern is preferably selected, considering the ease with which the user can follow the pattern.
  • the processing unit 51 recommends a desirable breathing pattern to the user via the output unit 25.
  • the processing unit 51 recommends a specific breathing pattern, saying "breathe in for five or more seconds, ten times", for example.
  • the user can control his/her blood pressure, using an appropriate breathing technique, and prevent a cardiovascular event from occurring.
  • the processing unit 51 may provide a breathing exercise function. For example, in a state where the respiration sensor and the biological information analysis system 10 are worn, the processing unit 51 provides a task, saying “breathe in for five or more seconds, ten times", for example, from the output unit 25. While the user is performing the task, the processing unit 51 monitors breathing and blood pressure, using the respiration sensor and the biological information analysis system 10, and evaluates whether or not the user is successfully breathing and controlling his/her blood pressure according to the task, and notifies the user of the results of evaluation via the output unit 25. Using such a function, the user can acquire a breathing technique in an objective manner.
  • a biological information analysis device comprising:
  • a biological information analysis system comprising:
  • a biological information analysis method comprising:

Abstract

A biological information analysis device includes: an indicator extraction unit configured to extract, from time-series data regarding blood pressure waveforms consecutively measured by a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat, and from time-series data regarding breathing measured by a respiration sensor during a period of time corresponding to the time-series data regarding blood pressure waveforms, an indicator indicating the relationship between the user's breathing and changes in blood pressure; and a processing unit configured to perform processing that is based on the indicator thus extracted.

Description

    TECHNICAL FIELD
  • The present invention relates to technology for acquiring useful information from a blood pressure waveform that has been measured.
  • RELATED ART
  • There is a known technology for measuring changes in the internal pressure of a radial artery and recording the shape of a pressure pulse wave (blood pressure waveform).
  • Patent Document 1 ( JP 2008-61824A ) discloses that a blood pressure waveform is measured using a tonometry method, and pieces of information such as an AI (Augmentation Index) value, a pulse wave period, a baseline fluctuation rate, sharpness, and an ET (Ejection Time) are acquired from the blood pressure waveform. Also, Patent Document 2 ( JP 2005-532111A ) discloses that a blood pressure waveform is measured using a wristwatch-type blood pressure meter, in which a mean arterial pressure, a mean systolic pressure, a mean diastolic pressure, a mean systolic pressure indicator, and a mean diastolic pressure indicator are calculated from the blood pressure waveform, and an alert is output when any of these values deviates from a reference value.
  • RELATED ART DOCUMENTS PATENT DOCUMENTS
    • Patent Document 1: JP 2008-61824A
    • Patent Document 2: JP 2005-532111A
    SUMMARY OF THE INVENTION PROBLEM TO BE SOLVED BY THE INVENTION
  • It is known that blood pressure can be controlled by using a breathing technique. However, it is envisioned that the amount of change in blood pressure varies for each person due to the influence of the characteristics and the disease state of each person, even if the same breathing pattern is used. Therefore, a standard routine for improvement in breathing does not have a sufficient blood pressure control effect. Also, for example, when a user experiences an increase in blood pressure or poor physical condition, even if the user knows that blood pressure can be controlled by using a breathing technique, the user does not know what specific measures can be taken.
  • The inventors of the present invention have worked hard to develop a blood pressure measurement device that can accurately measure an ambulatory blood pressure waveform for each heartbeat, and to put such a device into practical use. Through experiments performed on subjects during the development phase, the inventors have found that it can be possible to quantitatively evaluate a relationship between breathing and changes in blood pressure by accurately and non-invasively monitoring ambulatory blood pressure waveforms for each heartbeat.
  • Therefore, the present invention aims to provide a novel technology for acquiring information regarding a relationship between breathing and changes in blood pressure.
  • MEANS FOR SOLVING THE PROBLEMS
  • To achieve the above-described aim, the present invention employs the following configurations.
  • A biological information analysis device according to the present invention is a biological information analysis device that includes: an indicator extraction unit configured to extract, from time-series data regarding blood pressure waveforms consecutively measured by a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat, and from time-series data regarding breathing measured by a respiration sensor during a period of time corresponding to the time-series data regarding blood pressure waveforms, an indicator indicating a relationship between the user's breathing and changes in blood pressure; and a processing unit configured to perform processing that is based on the indicator thus extracted.
  • With the configuration according to the present invention, analysis is performed using time-series data regarding blood pressure waveforms measured from each heartbeat of the user, and time-series data regarding breathing measured during a period corresponding thereto. Therefore, it is possible to quantitatively analyze a relationship (a cause-effect relationship or a correlation) between breathing and change in blood pressure, which is a characteristic that is unique to the user.
  • It is preferable that the indicator extraction unit is configured to specify a plurality of periods of time that have the same breathing pattern, from the time-series data regarding breathing, and extract an indicator indicating the relationship between breathing and changes in blood pressure for the breathing pattern, from pieces of data regarding blood pressure waveforms respectively corresponding to the plurality of periods of time. By analyzing pieces of data regarding blood pressure waveforms corresponding to periods of time that have the same breathing pattern, it is possible to improve the reliability and objectivity of the indicator. For example, it is preferable that the indicator extraction unit is configured to extract, as the indicator, a trend in changes in blood pressure and/or the amount of changes that is/are common to pieces of data regarding blood pressure waveforms.
  • It is also preferable that the indicator extraction unit is configured to classify ways the user breathes, into a plurality of breathing patterns, based on the time-series data regarding the user's breathing. By classifying the user's breathing into a plurality of breathing patterns based on time-series data regarding the user's breathing, it is possible to acquire breathing patterns that are suitable for the user's characteristics.
  • For example, it is preferable that the time-series data regarding breathing includes, for each of a plurality of periods of time that include an exhalation period and an inhalation period, the length of the period of time and/or the amount of breath. If this is the case, the indicator extraction unit is configured to classify the plurality of periods of time into a plurality of breathing patterns based on the length of the period of time and/or the amount of breath. This is because the influence on blood pressure varies depending on the length of time spent for exhaling and inhaling and the amount of breath that is exhaled and inhaled.
  • It is preferable that the indicator extraction unit is configured to extract an indicator indicating the relationship between breathing and changes in blood pressure for each of the plurality of breathing patterns. By identifying the relationship between breathing and changes in blood pressure for each of the plurality of breathing patterns, it is possible to acquire information that is very useful for knowing characteristics of the user's respiratory and circulatory organs.
  • For example, it is preferable that the processing unit is configured to perform processing to output information representing the relationship between the user's breathing and changes in blood pressure, based on the indicator. Because such information is provided, the user can understand the relationship between his/her breathing and changes in blood pressure, and recognize an effective way of breathing when regulating blood pressure.
  • It is also preferable that the indicator extraction unit is configured to generate, for each of the plurality of breathing patterns, a relationship table that defines an indicator indicating the relationship between breathing and changes in blood pressure, and the processing unit is configured to select a breathing pattern that is to be followed in order to achieve a desired change in blood pressure, based on the relationship table, and recommend the selected breathing pattern to the user. With this configuration, it is possible to suggest an appropriate breathing pattern according to the user's characteristics and aim. Therefore, the user can effectively control his/her blood pressure by using a breathing technique.
  • It is preferable that the indicator extraction unit includes, as changes in blood pressure, at least one of: changes in systolic blood pressure; changes in diastolic blood pressure; changes in an AI (Augmentation Index); changes in the number of times a surge in blood pressure occurs; and changes in the amount of an increase in a surge in blood pressure.
  • Note that the present invention can be interpreted as a biological information analysis device or system that is provided with at least one of the above-described configurations or at least one of the above-described functions. The present invention can also be interpreted as a biological information analysis method that includes at least part of the above-described processing, or a program that causes a computer to execute such a method, or a computer-readable recording medium on which such a program is recorded in a non-transitory manner. The present invention can be formed by combining the above-described configurations and the above-described kinds of processing with each other unless no technical inconsistency occurs.
  • EFFECTS OF THE INVENTION
  • According to the present invention, it is possible to provide a novel technology for acquiring information regarding a relationship between breathing and changes in blood pressure.
  • BRIEF DESCRIPTION OF THE DRAWINGS
    • FIG. 1 shows a schematic external configuration of a biological information analysis system 10.
    • FIG. 2 is a block diagram showing a hardware configuration of the biological information analysis system 10.
    • FIG. 3 is a cross-sectional view schematically showing a configuration of a blood pressure measurement unit 20 and a state in which measurement is performed.
    • FIG. 4 shows a blood pressure waveform that is measured by the blood pressure measurement unit 20.
    • FIG. 5 is a block diagram illustrating processing that is performed by a biological information analysis device 1.
    • FIG. 6 shows a waveform (a blood pressure waveform) of a pressure pulse wave from a radial artery corresponding to one heartbeat.
    • FIG. 7 is a flowchart for processing that is performed to represent a relationship between breathing and changes in blood pressure as an indicator according to Example 1.
    • FIG. 8 is a diagram illustrating analysis of the relationship between breathing and changes in blood pressure according to Example 1.
    • FIGS 9A and 9B are diagrams showing an example of a relationship table that shows the relationship between breathing and changes in blood pressure according to Example 1.
    EMBODIMENTS OF THE INVENTION
  • The following describes a preferred embodiment of the present invention with reference to the drawings. Note that the following descriptions of components may be modified as appropriate depending on the configuration of a device to which the present invention is applied, and on various conditions, and the scope of the present invention is not intended to be limited to the following descriptions.
  • Biological Information Analysis System
  • FIG. 1 shows a schematic external configuration of a biological information analysis system 10 according to an embodiment of the present invention. FIG. 1 shows a state in which the biological information analysis system 10 is worn on the left wrist. The biological information analysis system 10 includes a main body 11 and a belt 12 that is fixed to the main body 11. The biological information analysis system 10 is a so-called wearable device, and is worn such that the main body 11 is in contact with the skin on the palm side of the wrist, and the main body 11 is located over a radial artery TD that lies beneath the skin. Although the device is configured to be worn on the radial artery TD in the present embodiment, the device may be configured to be worn on another superficial artery.
  • FIG. 2 is a block diagram showing a hardware configuration of the biological information analysis system 10. In general, the biological information analysis system 10 includes a measurement unit 2 and the biological information analysis device 1. The measurement unit 2 is a device that performs measurement to acquire information that is used to analyze biological information, and includes a blood pressure measurement unit 20, a body movement measurement unit 21, an environment measurement unit 22, and a respiration measurement unit 28. However, note that the configuration of the measurement unit 2 is not limited to that shown in FIG. 2. For example, a unit that measures biological information other than blood pressure or a body movement (e.g. body temperature, blood-sugar level, or brain waves) may be added. Also, any unit that is not used in the example described below is not an essential component, and may be omitted from the biological information analysis system 10. The biological information analysis device 1 is a device that analyzes biological information based on information acquired from the measurement unit 2, and includes a control unit 23, an input unit 24, an output unit 25, a communication unit 26, and a storage unit 27. The units 20 to 27 are connected to each other so that signals can be exchanged between them via a local bus or other signal lines. The biological information analysis system 10 also includes a power supply (a battery), which is not shown.
  • The blood pressure measurement unit 20 measures a pressure pulse wave from the radial artery TD by using a tonometry method. The tonometry method is for forming a flat area in the artery TD by pressing the artery from the skin with appropriate pressure, adjusting the balance between the internal pressure and the external pressure of the artery, and non-invasively measuring the pressure pulse wave using a pressure sensor.
  • The body movement measurement unit 21 includes a tri-axis acceleration sensor, and measures the movement of the user's body (body movement) using this sensor. The body movement measurement unit 21 may include a circuit that converts the format of an output from the tri-axis acceleration sensor into a format that is readable to the control unit 23.
  • The environment measurement unit 22 measures environmental information that may affect mental and physical conditions of the user (in particular the blood pressure). The environment measurement unit 22 may include, for example, an atmospheric temperature sensor, a humidity sensor, an illuminance sensor, an altitude sensor, a position sensor, and so on. The environment measurement unit 22 may include a circuit that converts the format of outputs from these sensors and so on into a format that is readable to the control unit 23.
  • The respiration measurement unit 28 is a unit that measures the state of the user's breathing. The respiration measurement unit 28 may include, for example, a respiration sensor such as a flow sensor. The respiration measurement unit 28 can at least discern between exhalation and inhalation, and measure the duration of exhalation and the duration of inhalation, and preferably, it can also measure the amount of breath. The respiration measurement unit 28 may include a circuit that converts the format of outputs from the respiration sensor and so on into a format that is readable to the control unit 23.
  • The control unit 23 performs various kinds of processing, such as controlling each unit of the biological information analysis system 10, acquiring data from the measurement unit 2, storing the acquired data in the recording unit 27, processing and analyzing data, and inputting and outputting data. The control unit 23 includes a hardware processor (hereinafter referred to as the "CPU") a ROM (Read Only Memory), a RAM (Random Access Memory), and so on. Processing that is performed by the control unit 23, which will be described later, is realized by the CPU reading and executing a program stored in the ROM or the storage unit 27. The RAM functions as a work memory that is used by the control unit 23 when performing various kinds of processing. Although acquisition of data from the measurement unit 2 and the storing of data in the storage unit 27 are performed by the control unit 23 in the present embodiment, it is possible to employ a configuration in which the measurement unit 2 directly stores (writes) data in the storage unit 27.
  • Each of the constituent components of the embodiment such as a measurement unit, an indicator extraction unit, a processing unit, a determination unit, a risk database, an input unit, an output unit, a case database, and so on may be implemented as pieces of hardware in the biological information analysis system 10. The indicator extraction unit, the processing unit, and the determination unit may receive an executable program stored in the storage unit 27, and execute the program. The indicator extraction unit, the processing unit, and the determination unit may receive data from the blood pressure measurement unit 20, the body movement measurement unit 21, the environment measurement unit 22, the input unit 24, the output unit 25, the communication unit 26, the storage unit 27, and so on as required. Databases such as the risk database and the case database may be implemented using the storage unit 27 and so on, and store pieces of information that are arranged such that a data search and data accumulation can be easily performed. Here, for example, the configuration, operations, and so on of the biological information analysis system 10 are disclosed in JP 2016-082069A . The contents of this disclosure are incorporated herein by reference. Also, the configuration, operations, and so on of the blood pressure measurement unit are disclosed in JP 2016-087003A . The contents of this disclosure are incorporated herein by reference.
  • The input unit 24 provides an operation interface for the user. For example, an operation button, a switch, a touch panel, and so on may be used.
  • The output unit 25 provides an interface that outputs information to the user. For example, a display device (such as a liquid crystal display) that outputs information using images, an audio output device or a beeper that outputs information using audio, an LED that outputs information by blinking, a vibration device that outputs information by vibrating, and so on may be used.
  • The communication unit 26 performs data communication with another device. Any data communication method such as a wireless LAN or Bluetooth (registered trademark) may be used.
  • The storage unit 27 is a storage medium that can store data and from which data can be read out, and stores programs that are to be executed by the control unit 23, pieces of measurement data acquired from the measurement units, and various kinds of data acquired by processing the pieces of measurement data, and so on. The storage unit 27 is a medium that accumulates pieces of information that are to be stored, through an electrical, magnetic, optical, mechanical, or chemical action. For example, a flash memory is used. The storage unit 27 may be a portable unit such as a memory card, or built into the biological information analysis system 10.
  • At least one unit or all units out of the body movement measurement unit 21, environment measurement unit 22, the control unit 23, the input unit 24, the output unit 25, and the storage unit 27 may be configured as a device that is separate from the main body 11. That is, as long as the blood pressure measurement unit 20 and the main body 11 that incorporates a circuit that controls the blood pressure measurement unit 20 are configured to be wearable on a wrist, the configurations of other units can be freely designed. If this is the case, the main body 11 cooperates with another unit via the communication unit 26. Various configurations can be conceived of. For example, the functions of the control unit 23, the input unit 24, and the output unit 25 may be realized using a smartphone application, and required data may be acquired from an activity monitor that has the functions of the body movement measurement unit 21 and the environment measurement unit 22. Also, a sensor that measures biological information other than blood pressure may be provided. For example, a sleep sensor, a pulse oximeter (SpO2 sensor), a blood-sugar level sensor, and the like may be combined.
  • Although the sensor (the blood pressure measurement unit 20) that measures blood pressure and the component (including the control unit 23 and so on) that performs processing to analyze blood pressure waveform data are provided in one device in the present embodiment, they may be provided in separate members. In the present embodiment, the component (including the control unit 23 and so on) that performs processing to analyze biological information is referred to as a biological information analysis device, and the device that includes the combination of the measurement unit and the biological information analysis device is referred to as a biological information analysis system. However, these names are given for descriptive purposes, and the measurement unit and the component that performs processing to analyze biological information may be referred to as a biological information analysis device as a whole, or other names may be used.
  • Measurement of Blood Pressure Waveform
  • FIG. 3 is a cross-sectional view schematically showing the configuration of the blood pressure measurement unit 20 and a state in which measurement is performed. The blood pressure measurement unit 20 includes a pressure sensor 30 and a pressurizing mechanism 31 for pressing the pressure sensor 30 against a wrist. The pressure sensor 30 includes a plurality of pressure detection elements 300. The pressure detection elements 300 detect pressure and convert the pressure into an electrical signal. For example, elements that utilize a piezoresistive effect may be preferably used. The pressurizing mechanism 31 includes, for example, an air bag and a pump that adjusts the internal pressure of the air bag. As a result of the control unit 23 controlling the pump to increase the internal pressure of the air bag, the air bag expands and the pressure sensor 30 is pressed against the surface of the skin. Note that the pressurizing mechanism 31 may be any mechanism as long as it can adjust the pressing force of the pressure sensor 30 applied to the surface of the skin, and is not limited to a mechanism that uses an air bag.
  • Upon the biological information analysis system 10 being worn on a wrist and activated, the control unit 23 controls the pressurizing mechanism 31 of the blood pressure measurement unit 20 to keep the pressing force of the pressure sensor 30 in an appropriate state (a tonometry state). Then, pressure signals detected by the pressure sensor 30 are sequentially acquired by the control unit 23. Pressure signals acquired from the pressure sensor 30 are generated by digitizing analogue physical amounts (e.g. voltage values) output by the pressure detection elements 300, through an A/D converter circuit or the like that employs a well-known technology. Preferable analogue values such as current values or resistance values may be employed as the analogue physical amounts, depending on the type of the pressure detection elements 300. Signal processing such as the aforementioned A/D conversion may be performed using a predetermined circuit provided in the blood pressure measurement unit 20, or performed by another unit (not shown) provided between the blood pressure measurement unit 20 and the control unit 23. Each pressure signal acquired by the control unit 23 corresponds to an instantaneous value of the internal pressure of the radial artery TD. Therefore, it is possible to acquire time-series data regarding blood pressure waveforms by acquiring pressure signals with time granularity and continuity that make it possible to ascertain a blood pressure waveform for each heartbeat. The control unit 23 stores the pressure signals sequentially acquired from the pressure sensor 30, in the storage unit 27, together with information regarding points in time at which the pressure signals were measured. The control unit 23 may store the acquired pressure signals in the storage unit 27 without change, or store the pressure signals in the storage unit 27 after performing required signal processing on the pressure signals. Required signal processing includes, for example, processing that is performed to calibrate each pressure signal such that the amplitude of the pressure signal matches the blood pressure value (e.g. the brachial blood pressure), processing that is performed to reduce or remove noise in each pressure signal, and so on.
  • FIG. 4 shows a blood pressure waveform measured by the blood pressure measurement unit 20. The horizontal axis indicates time and the vertical axis indicates blood pressure. Although the sampling frequency may be set to any value, it is preferably set to be no less than 100 Hz so that characteristics of the shape of a waveform corresponding to one heartbeat can be reproduced. Typically, the period of one heartbeat is approximately one second, and therefore approximately one hundred or more data points can be acquired on a waveform corresponding to one heartbeat.
  • The blood pressure measurement unit 20 according to the present embodiment is advantageous in terms of the following.
  • The blood pressure measurement unit 20 can measure a blood pressure waveform for each heartbeat. As a result, it is possible to acquire various indicators related to blood pressure, the state of the heart, cardiovascular risks, and so on, based on the characteristics of the shape of the blood pressure waveform. In addition, it is possible to monitor for instantaneous values of blood pressure. Therefore, it is possible to instantaneously detect a blood pressure surge (a sudden rise in the blood pressure value), and to detect changes in blood pressure and irregularities in a blood pressure waveform that may occur in a very short period of time (corresponding to one to several heartbeats) without missing them.
  • As a portable blood pressure meter, a blood pressure meter that is to be worn on a wrist or an upper arm and employs an oscillometric method to measure blood pressure has come into practical use. However, a conventional portable blood pressure meter can only measure the mean value of blood pressure based on changes in the internal pressure of a cuff during a period of several seconds to a dozen or so seconds corresponding to a plurality of heartbeats, and cannot acquire time-series data regarding a blood pressure waveform for each heartbeat, unlike the blood pressure measurement unit 20 according to the present embodiment.
  • The blood pressure measurement unit 20 can record time-series data regarding blood pressure waveforms. By acquiring time-series data regarding blood pressure waveforms, and, for example, discerning characteristics of the blood pressure waveform related to temporal changes, or performing a frequency analysis on the time-series data to extract a specific frequency component, it is possible to acquire various indicators related to blood pressure, the state of the heart, cardiovascular risks, and so on.
  • The device employs a portable (wearable) type configuration, and less burden is placed on the user during measurement. Therefore, continuous measurement for a long time, and even 24-hour blood pressure monitoring, can be relatively easily performed. Also, since the device is of a portable type, changes in not only blood pressure under resting conditions, but also an ambulatory blood pressure (for example, during daily life or exercise) can be measured. As a result, it is possible to grasp how blood pressure is affected by behaviours in daily life (such as sleeping, eating, commuting, working, and taking medicine) and exercise, for example.
  • Conventional products are types of devices that measure blood pressure under resting conditions, with an arm or a wrist fixed to a blood pressure measurement unit, and cannot measure changes in blood pressure in daily life or during exercise, unlike the biological information analysis system 10 according to the present embodiment.
  • The blood pressure measurement unit 20 can be easily combined or linked with other sensors. For example, it is possible to make an evaluation of a cause-effect relationship or a composite evaluation with information that can be acquired by other sensors (e.g. a body movement, environmental information such as an atmospheric temperature, biological information such as SpO2 and respiration information).
  • Biological Information Analysis Device
  • FIG. 5 is a block diagram illustrating processing that is performed by the biological information analysis device 1. As shown in FIG. 5, the biological information analysis device 1 includes an indicator extraction unit 50 and a processing unit 51. In the present embodiment, processing performed by the indicator extraction unit 50 and the processing unit 51 may be realized by the control unit 23 executing a program that is required for the processing. The program may be stored in the storage unit 27. When the control unit 23 executes the required program, the subject program stored in the ROM or storage unit 27 is loaded to the RAM. Then, the control unit 23 interprets and executes the program loaded to the RAM, using the CPU, to control each constituent component. Note that at least one or all of the processing procedures executed by the indicator extraction unit 50 and the processing unit 51 may be realized using a circuit such as an ASIC or an FPGA. Alternatively, at least one or all of the processing procedures executed by the indicator extraction unit 50 and the processing unit 51 may be realized using a computer (e.g. a smartphone, a tablet terminal, a personal computer, or a cloud server) that is separate from the main body 11.
  • The indicator extraction unit 50 acquires time-series data regarding blood pressure waveforms, which have been consecutively measured by the blood pressure measurement unit 20, from the storage unit 27. The indicator extraction unit 50 extracts, from the acquired time-series data regarding blood pressure waveforms, indicators that are related to characteristics of the blood pressure waveforms. Here, characteristics of a blood pressure waveform include, for example, characteristics of the shape of a blood pressure waveform corresponding to one heartbeat, temporal changes in a blood pressure waveform, and frequency components of a blood pressure waveform. However, characteristics of a blood pressure waveform are not limited to those listed above. The extracted indicators are output to the processing unit 51. There are various characteristics and indicators regarding a blood pressure waveform, and the characteristics and indicators that are to be extracted may be designed or selected as appropriate according to the purpose of processing that is to be performed by the processing unit 51. Characteristics and indicators that can be extracted from measurement data regarding blood pressure waveforms according to the present embodiment will be described later in detail.
  • When obtaining indicators, the indicator extraction unit 50 may use measurement data that has been acquired by the body movement measurement unit 21 and/or measurement data that has been acquired by the environment measurement unit 22, in addition to measurement data regarding blood pressure waveforms. Also, although not shown in the drawings, pieces of measurement data that have been acquired by a sleep sensor, an SpO2 sensor, a blood-sugar level sensor, and the like may be combined with one another. By performing complex analysis on a plurality of kinds of measurement data acquired by a plurality of sensors, it is possible to perform more advanced information analysis of a blood pressure waveform. For example, it is possible to classify pieces of data regarding blood pressure waveforms according to states of the user, such as a resting state and a moving state, a state when an atmospheric temperature is high and a state when it is low, a light sleep state and a deep sleep state, a breathing state and an apnea state, and so on. Alternatively, it is possible to extract information regarding the influence of body movement, an activity amount, activity intensity, a change in an atmospheric temperature, apnea, the user's breathing, etc. on blood pressure, and thus evaluate the cause-effect relationship, the correlation, etc. between pieces of measurement data.
  • The processing unit 51 receives the indicators extracted by the indicator extraction unit 50. The processing unit 51 performs processing that is based on the received indicators. Various kinds of processing can be conceived of as processing that is based on the indicators. For example, the processing unit 51 may provide the values of the extracted indicators or changes in the values to a user, a doctor, a public health nurse, or the like to prompt the utilization of the indicators in the fields of health care, treatment, health guidance, and so on. Alternatively, the processing unit 51 may estimate cardiovascular risks from the extracted indicators, or provide guidelines for health maintenance or risk mitigation. Furthermore, when an increase in the risk of a cardiac disease occurring is detected or predicted based on an indicator, the processing unit 51 may inform the user or his/her doctor, or perform control to prevent the user from performing an action that burdens his/her heart and so on, or to prevent a cardiovascular event from occurring.
  • Information Acquired from Blood Pressure Waveform
  • FIG. 6 shows a waveform (a blood pressure waveform) of a pressure pulse wave from a radial artery corresponding to one heartbeat. The horizontal axis indicates time t (msec) and the vertical axis indicates blood pressure BP (mmHg).
  • A blood pressure waveform is the waveform of a composite wave constituted by an "ejection wave" that is generated when the heart contracts and pumps out blood, and a "reflection wave" that is generated when an ejection wave is reflected at a branch point of a peripheral vessel or an artery. The following shows examples of characteristic points that can be extracted from a blood pressure waveform corresponding to one heartbeat.
    • A point F1 is the rising point of the pressure pulse wave. The point F1 corresponds to the ejection start point of the heart, i.e. the point at which the aortic valve opens.
    • A point F2 is a point at which the amplitude (the pressure) of the ejection wave is at the maximum (a first peak).
    • A point F3 is an inflection point that appears midway in a drop in the ejection wave, due to a reflection wave being superimposed.
    • A point F4 is the minimum point, which appears between the ejection wave and the reflection wave, and is also referred to as a notch. This point corresponds to the point at which the aortic valve closes.
    • A point F5 is the peak of the reflection wave (a second peak), which appears after the point F4.
    • A point F6 is the end point of one heartbeat, and corresponds to the ejection start point of the next heartbeat, i.e. the start point of the next heartbeat.
  • The indicator extraction unit 50 may use any algorithm to detect the above-described characteristic points. For example, the indicator extraction unit 50 may perform computations to obtain an nth order differential waveform of a blood pressure waveform, and detect the zero-crossing points to extract the characteristic points (the inflection points) of the blood pressure waveform (the points F1, F2, F4, F5, and F6 can be detected from the first order differential waveform, and the point F3 can be detected from the second order differential waveform or the fourth order differential waveform). Alternatively, the indicator extraction unit 50 may read out, from the storage unit 27, a waveform pattern on which the characteristic points have been arranged in advance, and perform fitting of the waveform pattern to the target blood pressure waveform to specify the respective positions of the characteristic points.
  • The indicator extraction unit 50 performs computations based on time t and pressure BP of each of the above-described characteristic points F1 to F6, and can thus obtain various kinds of information (values, characteristic amounts, indicators, etc.) from the blood pressure waveform of one heartbeat. The following are typical examples of information that can be acquired from a blood pressure waveform. Note that tx and BPx respectively represent time and blood pressure corresponding to a characteristic point Fx.
    • Pulse Wave Interval (Period of Heartbeat) TA = t6 - t1
    • Heart Rate PR = 1/TA
    • Pulse Wave Rising Time UT = t2 - t1
    • Systole TS = t4 - t1
    • Diastole TD = t6 - t4
    • Reflection Wave Delay Time = t3 - t1
    • Maximum Blood Pressure (Systolic Blood Pressure) SBP = BP2
    • Minimum Blood Pressure (Diastolic Blood Pressure) DBP = BP1
    • Mean Blood Pressure MAP = (Area of Blood Pressure Waveform from t1 to t6)/Period of Heartbeat TA
    • Mean Blood Pressure during Systole = (Area of Blood Pressure Waveform from t1 to t4)/Systole TS
    • Mean Blood Pressure during Diastole = (Area of Blood Pressure Waveform from t4 to t6)/Diastole TD
    • Pulse Pressure PP = Maximum Blood Pressure SBP - Minimum Blood Pressure DBP
    • Late Systolic Pressure SBP2 = BP3
    • AI (Augmentation Index) = (Late Systolic Pressure SBP2 - Minimum Blood Pressure DBP)/Pulse Pressure PP
  • Basic statistics of these pieces of information (values, characteristic amounts, and indicators) can also be used as indicators. Basic statistics include, for example, representative values (a mean value, a median value, a mode value, the maximum value, the minimum value, and so on) and the degree of scatter (dispersion, a standard deviation, a coefficient of variation, and so on). Temporal changes in these pieces of information (values, characteristic values, and indicators) can also be used as indicators.
  • In addition, the indicator extraction unit 50 can also acquire an indicator called BRS (Baroreflex Sensitivity) by performing computations on pieces of heartbeat information. This indicator indicates the ability to regulate blood pressure to be constant. Examples of methods for calculating the indicator include a spontaneous sequence method. This is a method for only extracting a sequence in which the maximum blood pressure SBP and the pulse wave interval TA consecutively rise or fall over the period of three or more heartbeats in synchronization with each other, plotting the maximum blood pressure SBP and the pulse wave interval TA onto a two-dimensional plane, and defining the inclination of the regression line obtained through a least squares method as the BRS.
  • As described above, the use of the biological information analysis system 10 according to the present embodiment makes it is possible to acquire various kinds of information from blood pressure waveform data. However, the biological information analysis system 10 need not implement all of the functions that are required to acquire all of the kinds of information described above. The biological information analysis system 10 need only implement functions that are required to acquire necessary information, depending on the configuration of the biological information analysis system 10, who the user is, the purpose of use, the location of use, and so on. Also, each function may be provided as a program module (a piece of application software), and the biological information analysis system 10 may employ a mechanism with which a function can be added by installing a necessary program module on the biological information analysis system 10.
  • The following illustrates an example, which is a specific application, of the biological information analysis system 10.
  • Example 1
  • The present example proposes a method for suggesting a breathing technique that is suitable for the characteristics and the state of disease of each individual user in an objective manner by representing the relationship between breaths and changes in blood pressure based on time-series data regarding breathing and blood pressure measured from users.
  • Note that conventional blood pressure meters that employ an oscillometric method cannot accurately keep track of each breathing action, or the influence of each action of exhaling/inhaling on blood pressure, because a plurality of breathing actions are performed while blood pressure is measured once. In contrast, the device according to the present example can accurately and non-invasively measure a blood pressure waveform for each heartbeat, and is thus able to quantitatively analyze the influence of each action of exhaling/inhaling on blood pressure or the waveform thereof.
  • As shown in FIG. 2, the biological information analysis system 10 according to the present example includes a respiration sensor that serves as the respiration measurement unit 28. However, since it is only necessary to measure breathing and blood pressure waveforms in synchronization, the biological information analysis system 10 may not be provided with a respiration measurement unit, and the biological information analysis system 10 may simply use data measured by another respiration sensor. If this is the case, measurement data regarding blood pressure waveforms and measurement data acquired by the respiration sensor can be associated with each other in terms of time, based on measurement time information (time stamps), for example.
  • As a respiration sensor, a flow sensor that can detect the direction in which air flows, such as that disclosed in JP H10-185639A , can be favorably used. This flow sensor detects an air flow caused by the breathing action to determine whether the action is exhalation or inhalation. Alternatively, a pressure sensor or a vibration sensor may be used as a respiration sensor. If this is the case, body movement caused by the breathing action is detected by a pressure sensor, a vibration sensor, or the like that is attached to a body part, and thus the breathing action is indirectly detected.
  • FIG. 7 shows an example of a flowchart for processing according to the present example. First, in order to grasp the relationship between breathing and changes in blood pressure, the user wears the biological information analysis system 10 and the respiration sensor, and blood pressure waveforms and breathing are measured (step 4500). Time-series data regarding blood pressure waveforms and time-series data regarding breathing are stored in the storage unit 27. The time-series data regarding breathing includes pieces of information regarding exhalation periods (periods of time during which air is exhaled) and pieces of information regarding inhalation periods (periods of time during which air is inhaled), which are arranged one after the other. A piece of information regarding an exhalation period includes the start time and the end time of the period, the length of the period (also referred to as the duration of exhalation), and the amount of breath in the period (the amount of exhaled air, which is also referred to as an exhale amount). A piece of information regarding an inhalation period includes the start time and the end time of the period, the length of the period (also referred to as the duration of inhalation), and the amount of breath in the period (the amount of inhaled air, which is also referred to as an inhale amount).
  • Next, the indicator extraction unit 50 analyzes the relationship between breathing and changes in blood pressure (step 4501). Specifically, the indicator extraction unit 50 reads, from the storage unit 27, time-series data regarding blood pressure waveforms, and time-series data regarding breathing measured in the period corresponding to the time-series data regarding blood pressure waveforms. Thereafter, as shown in FIG. 8, the indicator extraction unit 50 specifies exhalation periods and inhalation periods based on the time-series data regarding breathing, and divides the time-series data regarding blood pressure waveforms into blood pressure waveforms respectively corresponding to the periods. Thereafter, the indicator extraction unit 50 performs data mining processing such as cross tabulation or regression analysis on pieces of information regarding breathing respectively corresponding to the periods, and information regarding blood pressure waveforms corresponding thereto, to extract an indicator indicating the relationship between breathing and changes in blood pressure.
  • For example, the indicator extraction unit 50 classifies (typifies) the ways the user breathes, into a plurality of patterns, based on information regarding breathing in each period. The classification into breathing patterns may be performed based on, for example, the length of the period and/or the amount of breath. Here, exhalation periods and inhalation periods may be classified so as to be separate from each other, or classified into sets each consisting of an exhalation period and an inhalation period (each set is referred to as a breathing period). Thereafter, the indicator extraction unit 50 may collect pieces of data regarding blood pressure waveforms for a plurality of periods that have the same breathing pattern, and extract, as indicators indicating the relationship between breathing and changes in blood pressure, a trend in changes in blood pressure (an increase, a decrease, no change, and so on) and/or the amount of changes (the amount of an increase, the amount of a decrease, and so on) that are/is common to the pieces of data regarding blood pressure waveforms. By performing the same processing for each breathing pattern, it is possible to obtain an indicator indicating the relationship between breathing and changes in blood pressure for each of a plurality of breathing patterns.
  • Here, "data regarding blood pressure waveforms corresponding to a given period" may be "data regarding blood pressure waveforms in the given period" or "data regarding blood pressure waveforms of a plurality of periods that include the period and one or more periods that are previous and/or subsequent to the period". In the former case, changes in blood pressure waveforms within one period (for example, an increase rate and a decrease rate of systolic blood pressure) are items that are to be used to evaluate changes in blood pressure. In the latter case, changes in blood pressure waveforms within a plurality of periods (for example, the amount of change in systolic blood pressure (SBP), the amount of change in diastolic blood pressure (DBP), the amount of change in AI (Augmentation Index), the amount of change in the number of times a surge in blood pressure has occurred, and the amount of change in the amount of increase in a surge in blood pressure) are items that are to be used to evaluate changes in blood pressure. Alternatively, as "data regarding blood pressure waveforms corresponding to a given period", "data regarding blood pressure waveforms measured upon a predetermined period of time elapsing after the period" may be used. Such an analysis is effective if the influence of breathing on blood pressure waveforms appears upon a predetermined period of time elapsing.
  • Next, the indicator extraction unit 50 stores the relationship between breathing and changes in blood pressure (an indicator) acquired in step 4501 for each breathing pattern, in the storage unit 27, in the form of a relationship table (step 4502). FIGS. 9A and 9B show an example of the relationship table. It can be seen from the relationship table shown in FIG. 9A that, if a small amount of air is inhaled in a short period of time, the SBP decreases by 10 mmHg, and if a large amount of air is inhaled even in a short period of time, the SBP decreases by 30 mmHg. Here, whether the duration of a period is long or short may be determined based on whether or not the duration of the period is longer than a threshold value. The threshold value is stored in the storage unit 27, for example. Similarly, whether the amount of breath is large or small may be determined based on whether or not the amount of breath in the period is greater than a threshold value. The threshold values may be fixed, or changed as appropriate according to the tendencies and the characteristics of the user. It can be seen from the relationship table shown in FIG. 9B that the SBP decreases by 4 mmHg per second during inhalation, and the SBP decreases by 10 mmHg per liter of breath. Note that tables shown in FIGS. 9A and 9B are examples, and it is also preferable that the amount of changes in the DBP and the amount changes in the AI are recorded. It can be said that these relationship tables are indicators indicating the relationship between breathing and change in blood pressure. The relationship tables thus generated are stored in the storage unit 27, and used for various kinds of processing that is performed by the processing unit 51.
  • Note that, if it is possible to use a past case database in which relationship tables are registered, which show the relationship between breathing and changes in blood pressure for a large number of subjects, the indicator extraction unit 50 may acquire, from the past case database, data of another subject who is similar to the user in terms of the relationship between breathing and changes in blood pressure, and generate a relationship table for the user, considering the data of the subject as well. Thus, it is possible to generate a more accurate and objective relationship table.
  • Next, the following describes an example of processing that is performed by the processing unit 51. For example, the processing unit 51 may read a relationship table stored in the storage unit 27, and output information representing the relationship between the user's breathing and changes in blood pressure, from the output unit 25. At this time, information representing the relationship between the user's breathing and changes in blood pressure may be output in the form of a table as shown in FIGS. 9A and 9B, or in a different form.
  • Also, the processing unit 51 may perform breathing pattern recommendation processing based on a relationship table. Breathing pattern recommendation processing is performed to suggest a breathing pattern that is to be followed in order to achieve a desired change in blood pressure. For example, it is envisioned that a user experiences an increase in blood pressure or poor physical condition, and wishes to regulate blood pressure by using a breathing technique. If this is the case, the user inputs a target value of a change in blood pressure, using the input unit 24 of the biological information analysis system 10. For example, it is envisioned that that user has entered a target value to "lower the systolic blood pressure (SBP) by 30 mmHg". The processing unit 51 refers to relationship tables in the storage unit 27, and designs a breathing pattern (the duration of exhalation, the duration of inhalation, an exhale amount, an inhale amount, the number of breaths, and so on) that is required to lower the SBP by 30 mmHg. At this time, if a plurality of kinds of breathing patterns can be conceived of, the most appropriate breathing pattern is preferably selected, considering the ease with which the user can follow the pattern.
  • Thereafter, the processing unit 51 recommends a desirable breathing pattern to the user via the output unit 25. For example, it is preferable that the processing unit 51 recommends a specific breathing pattern, saying "breathe in for five or more seconds, ten times", for example. As a result, the user can control his/her blood pressure, using an appropriate breathing technique, and prevent a cardiovascular event from occurring.
  • However, if the user is recommended to "breathe in for five or more seconds, ten times", there is the possibility of the user being unable to actually breathe as instructed. Therefore, the processing unit 51 may provide a breathing exercise function. For example, in a state where the respiration sensor and the biological information analysis system 10 are worn, the processing unit 51 provides a task, saying "breathe in for five or more seconds, ten times", for example, from the output unit 25. While the user is performing the task, the processing unit 51 monitors breathing and blood pressure, using the respiration sensor and the biological information analysis system 10, and evaluates whether or not the user is successfully breathing and controlling his/her blood pressure according to the task, and notifies the user of the results of evaluation via the output unit 25. Using such a function, the user can acquire a breathing technique in an objective manner.
  • The configurations according to the above-described embodiment and examples are no more than specific examples of configurations according to the present invention, and are not intended to limit the scope of the present invention. The present invention may employ various specific configurations without departing from the technical idea thereof.
  • The technical idea disclosed in the present description can be specified as the following aspects of the present invention.
  • Supplementary Note 1
  • A biological information analysis device comprising:
    • a hardware processor; and a memory that is configured to store a program,
    • wherein the hardware processor is configured to execute the program to
    • extract, from time-series data regarding blood pressure waveforms consecutively measured by a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat, and from time-series data regarding breathing measured by a respiration sensor during a period of time corresponding to the time-series data regarding blood pressure waveforms, an indicator indicating the relationship between the user's breathing and changes in blood pressure, and
    • perform processing that is based on the indicator thus extracted.
    Supplementary Note 2
  • A biological information analysis system comprising:
    • a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat; a hardware processor; and a memory that is configured to store a program,
    • wherein the hardware processor is configured to execute the program to
    • extract, from time-series data regarding blood pressure waveforms consecutively measured by a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat, and from time-series data regarding breathing measured by a respiration sensor during a period of time corresponding to the time-series data regarding blood pressure waveforms, an indicator indicating the relationship between the user's breathing and changes in blood pressure, and
    • perform processing that is based on the indicator thus extracted.
    Supplementary Note 3
  • A biological information analysis method comprising:
    • a step of extracting, from time-series data regarding blood pressure waveforms consecutively measured by a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat, and from time-series data regarding breathing measured by a respiration sensor during a period of time corresponding to the time-series data regarding blood pressure waveforms, an indicator indicating the relationship between the user's breathing and changes in blood pressure, using at least one hardware processor; and
    • a step of performing processing that is based on the indicator thus extracted, using at least one hardware processor.
    INDEX TO THE REFERENCE NUMERALS
  • 1 ... biological information analysis device, 2 ... measurement unit 10 ... biological information analysis system, 11 ... main body, 12 ... belt 20 ... blood pressure measurement unit, 21 ... body movement measurement unit, 22 ... environment measurement unit, 23 ... control unit, 24 ... input unit, 25 ... output unit, 26 ... communication unit, 27 ... storage unit, 28 ... respiration measurement unit 30 ... pressure sensor, 31 ... pressurizing mechanism, 300 ... pressure detection element 50 ... indicator extraction unit, 51 ... processing unit

Claims (13)

  1. A biological information analysis device comprising:
    an indicator extraction unit configured to extract, from time-series data regarding blood pressure waveforms consecutively measured by a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat, and from time-series data regarding breathing measured by a respiration sensor during a period of time corresponding to the time-series data regarding blood pressure waveforms, an indicator indicating a relationship between the user's breathing and changes in blood pressure; and
    a processing unit configured to perform processing that is based on the indicator thus extracted.
  2. The biological information analysis device according to claim 1,
    wherein the indicator extraction unit is configured to specify a plurality of periods of time that have the same breathing pattern, from the time-series data regarding breathing, and extract an indicator indicating the relationship between breathing and changes in blood pressure for the breathing pattern, from pieces of data regarding blood pressure waveforms respectively corresponding to the plurality of periods of time.
  3. The biological information analysis device according to claim 2,
    wherein the indicator extraction unit is configured to extract, as the indicator, a tendency in changes in blood pressure and/or the amount of changes that is/are common to pieces of data regarding blood pressure waveforms.
  4. The biological information analysis device according to claim 2 or 3,
    wherein the indicator extraction unit is configured to classify ways the user breathes, into a plurality of breathing patterns, based on the time-series data regarding the user's breathing.
  5. The biological information analysis device according to claim 4,
    wherein the time-series data regarding breathing includes, for each of a plurality of periods of time that include an exhalation period and an inhalation period, the length of the period of time and/or the amount of breath, and
    the indicator extraction unit is configured to classify the plurality of periods of time into a plurality of breathing patterns based on the length of the period of time and/or the amount of breath.
  6. The biological information analysis device according to claim 4 or 5,
    wherein the indicator extraction unit is configured to extract an indicator indicating the relationship between breathing and changes in blood pressure for each of the plurality of breathing patterns.
  7. The biological information analysis device according to any one of claims 1 to 6,
    wherein the processing unit is configured to perform processing to output information representing the relationship between the user's breathing and changes in blood pressure, based on the indicator.
  8. The biological information analysis device according to claim 6,
    wherein the indicator extraction unit is configured to generate, for each of the plurality of breathing patterns, a relationship table that defines an indicator indicating the relationship between breathing and changes in blood pressure, and
    the processing unit is configured to select a breathing pattern that is to be followed in order to achieve a desired change in blood pressure, based on the relationship table, and recommend the selected breathing pattern to the user.
  9. The biological information analysis device according to any one of claims 1 to 8,
    wherein the indicator extraction unit includes, as changes in blood pressure, at least one of: changes in systolic blood pressure; changes in diastolic blood pressure; changes in an AI (Augmentation Index); changes in the number of times a surge in blood pressure occurs; and changes in the amount of an increase in a surge in blood pressure.
  10. A biological information analysis system comprising:
    a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat; and
    the biological information analysis device according to any one of claims 1 to 9, the biological information analysis device being configured to analyze biological information, using data regarding blood pressure waveforms consecutively measured by the sensor.
  11. The biological information analysis system according to claim 10, further comprising:
    a respiration sensor.
  12. A program that causes a processor to function as the indicator extraction unit and the processing unit of the biological information analysis device according to any one of claims 1 to 9.
  13. A biological information analysis method comprising:
    a step of extracting, from time-series data regarding blood pressure waveforms consecutively measured by a sensor that is configured to be worn on a body part of a user and to be capable of non-invasively measuring a blood pressure waveform for each heartbeat, and from time-series data regarding breathing measured by a respiration sensor during a period of time corresponding to the time-series data regarding blood pressure waveforms, an indicator indicating a relationship between the user's breathing and changes in blood pressure; and
    a step of performing processing that is based on the indicator thus extracted.
EP17782515.5A 2016-04-15 2017-04-14 Biological information analysis device, system, and program Active EP3427653B1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2016082463 2016-04-15
PCT/JP2017/015283 WO2017179702A1 (en) 2016-04-15 2017-04-14 Biological information analysis device and system, and program

Publications (3)

Publication Number Publication Date
EP3427653A1 true EP3427653A1 (en) 2019-01-16
EP3427653A4 EP3427653A4 (en) 2019-12-11
EP3427653B1 EP3427653B1 (en) 2021-03-31

Family

ID=60041783

Family Applications (11)

Application Number Title Priority Date Filing Date
EP17782507.2A Active EP3430989B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, program, and biological information analysis method
EP17782514.8A Active EP3427652B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, and program
EP17782515.5A Active EP3427653B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, and program
EP17782513.0A Active EP3427656B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, and program
EP17782516.3A Ceased EP3427654A4 (en) 2016-04-15 2017-04-14 Biological information analysis device and system, and program
EP17782510.6A Active EP3427650B1 (en) 2016-04-15 2017-04-14 Biological information analyzing device, system, and program
EP17782511.4A Pending EP3427651A4 (en) 2016-04-15 2017-04-14 Biological information analysis device and system, and program
EP17782509.8A Active EP3427655B1 (en) 2016-04-15 2017-04-14 Biological information analyzing device, system, and program
EP17782506.4A Pending EP3427648A4 (en) 2016-04-15 2017-04-14 Biological information analysis device, biological information analysis system, program, and biological information analysis method
EP17782508.0A Active EP3427649B1 (en) 2016-04-15 2017-04-14 Biological information analyzing device, system, and program
EP17782512.2A Active EP3440995B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, and program

Family Applications Before (2)

Application Number Title Priority Date Filing Date
EP17782507.2A Active EP3430989B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, program, and biological information analysis method
EP17782514.8A Active EP3427652B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, and program

Family Applications After (8)

Application Number Title Priority Date Filing Date
EP17782513.0A Active EP3427656B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, and program
EP17782516.3A Ceased EP3427654A4 (en) 2016-04-15 2017-04-14 Biological information analysis device and system, and program
EP17782510.6A Active EP3427650B1 (en) 2016-04-15 2017-04-14 Biological information analyzing device, system, and program
EP17782511.4A Pending EP3427651A4 (en) 2016-04-15 2017-04-14 Biological information analysis device and system, and program
EP17782509.8A Active EP3427655B1 (en) 2016-04-15 2017-04-14 Biological information analyzing device, system, and program
EP17782506.4A Pending EP3427648A4 (en) 2016-04-15 2017-04-14 Biological information analysis device, biological information analysis system, program, and biological information analysis method
EP17782508.0A Active EP3427649B1 (en) 2016-04-15 2017-04-14 Biological information analyzing device, system, and program
EP17782512.2A Active EP3440995B1 (en) 2016-04-15 2017-04-14 Biological information analysis device, system, and program

Country Status (5)

Country Link
US (11) US20190117084A1 (en)
EP (11) EP3430989B1 (en)
JP (11) JP6687263B2 (en)
CN (11) CN108882870B (en)
WO (11) WO2017179697A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11882755B2 (en) 2019-04-12 2024-01-23 Semiconductor Energy Laboratory Co., Ltd. Display device and system

Families Citing this family (75)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP7124460B2 (en) * 2018-05-31 2022-08-24 セイコーエプソン株式会社 Biological analysis device, biological analysis method and program
US11116414B2 (en) * 2017-08-16 2021-09-14 Seiko Epson Corporation Biological analysis device, biological analysis method, and program
US11253205B2 (en) * 2017-08-16 2022-02-22 Seiko Epson Corporation Pulse pressure and blood pressure analysis device, pulse pressure and blood pressure analysis method, and program
US11317873B2 (en) * 2017-08-16 2022-05-03 Seiko Epson Corporation Biological analysis device, biological analysis method, and program
CN107550481A (en) * 2017-08-24 2018-01-09 京东方科技集团股份有限公司 A kind of portable equipment and blood pressure measuring method
CN109833037B (en) * 2017-11-29 2022-05-17 华为终端有限公司 Equipment for monitoring blood pressure state and computer readable storage medium
JP2019115602A (en) * 2017-12-27 2019-07-18 オムロンヘルスケア株式会社 Biological information measuring device, measurement control method, and program
JP6897558B2 (en) * 2017-12-27 2021-06-30 オムロンヘルスケア株式会社 Information processing equipment, information processing methods and information processing programs
US20200337578A1 (en) * 2018-01-09 2020-10-29 Rohini Shankar Wearable ecg and auscultation monitoring system with sos and remote monitoring
JP7091701B2 (en) * 2018-02-22 2022-06-28 オムロンヘルスケア株式会社 Blood pressure measuring device, blood pressure measuring method and program, breathing support device
JP6626951B2 (en) * 2018-03-12 2019-12-25 パラマウントベッド株式会社 Electric furniture
KR20200131289A (en) * 2018-06-05 2020-11-23 카즈오 타니 Blood flow measurement system
CN112638249A (en) * 2018-08-23 2021-04-09 深圳迈瑞生物医疗电子股份有限公司 Medical equipment, apnea event monitoring method and device
WO2020044523A1 (en) * 2018-08-30 2020-03-05 オリンパス株式会社 Recording device, image observation device, observation system, observation system control method, and observation system operating program
CN111012323A (en) * 2018-10-10 2020-04-17 三星电子株式会社 Device for estimating blood pressure and device for supporting blood pressure estimation
CN113164081A (en) * 2018-11-06 2021-07-23 三星电子株式会社 Electronic device and method for identifying the occurrence of hypotension
CN109674474B (en) * 2018-11-30 2021-12-03 深圳和而泰智能控制股份有限公司 Sleep apnea recognition method, device and computer readable medium
CN109731314B (en) * 2019-01-25 2020-12-29 杨彬 Cerebral infarction rehabilitation training device based on high in clouds
JP7320807B2 (en) * 2019-02-14 2023-08-04 デルタ工業株式会社 Physical condition determination device and computer program
JP7225893B2 (en) * 2019-02-18 2023-02-21 オムロンヘルスケア株式会社 Blood pressure value analysis support device, blood pressure value analysis support system, blood pressure value analysis support method, and program
JP7127571B2 (en) * 2019-02-18 2022-08-30 オムロンヘルスケア株式会社 Blood pressure level change detection device, blood pressure level change detection method, and program
US11471729B2 (en) 2019-03-11 2022-10-18 Rom Technologies, Inc. System, method and apparatus for a rehabilitation machine with a simulated flywheel
US20200289045A1 (en) 2019-03-11 2020-09-17 Rom Technologies, Inc. Single sensor wearable device for monitoring joint extension and flexion
JP6871546B2 (en) * 2019-03-12 2021-05-12 群馬県 Detection method and detection device for detecting abnormalities in pulse pressure waveform
JP7256049B2 (en) * 2019-03-25 2023-04-11 オムロンヘルスケア株式会社 Blood pressure-related information display device, blood pressure-related information display method, and program
JP7326802B2 (en) * 2019-03-25 2023-08-16 オムロンヘルスケア株式会社 Measurement facilitator, method and program
US11904207B2 (en) 2019-05-10 2024-02-20 Rehab2Fit Technologies, Inc. Method and system for using artificial intelligence to present a user interface representing a user's progress in various domains
US11433276B2 (en) 2019-05-10 2022-09-06 Rehab2Fit Technologies, Inc. Method and system for using artificial intelligence to independently adjust resistance of pedals based on leg strength
US11801423B2 (en) 2019-05-10 2023-10-31 Rehab2Fit Technologies, Inc. Method and system for using artificial intelligence to interact with a user of an exercise device during an exercise session
JP7328044B2 (en) * 2019-07-22 2023-08-16 マクセル株式会社 Detection device and detection method
KR102567952B1 (en) 2019-09-11 2023-08-16 삼성전자주식회사 Apparatus and method for estimating bio-information
JP2021040969A (en) * 2019-09-11 2021-03-18 オムロンヘルスケア株式会社 Method for generating determination algorithm, determination algorithm, determination system, determination method, program, and recording medium
US11701548B2 (en) 2019-10-07 2023-07-18 Rom Technologies, Inc. Computer-implemented questionnaire for orthopedic treatment
US11282604B2 (en) 2019-10-03 2022-03-22 Rom Technologies, Inc. Method and system for use of telemedicine-enabled rehabilitative equipment for prediction of secondary disease
US11756666B2 (en) 2019-10-03 2023-09-12 Rom Technologies, Inc. Systems and methods to enable communication detection between devices and performance of a preventative action
US11337648B2 (en) 2020-05-18 2022-05-24 Rom Technologies, Inc. Method and system for using artificial intelligence to assign patients to cohorts and dynamically controlling a treatment apparatus based on the assignment during an adaptive telemedical session
US11915815B2 (en) 2019-10-03 2024-02-27 Rom Technologies, Inc. System and method for using artificial intelligence and machine learning and generic risk factors to improve cardiovascular health such that the need for additional cardiac interventions is mitigated
US20210134458A1 (en) 2019-10-03 2021-05-06 Rom Technologies, Inc. System and method to enable remote adjustment of a device during a telemedicine session
US11139060B2 (en) 2019-10-03 2021-10-05 Rom Technologies, Inc. Method and system for creating an immersive enhanced reality-driven exercise experience for a user
US11515028B2 (en) 2019-10-03 2022-11-29 Rom Technologies, Inc. Method and system for using artificial intelligence and machine learning to create optimal treatment plans based on monetary value amount generated and/or patient outcome
US11830601B2 (en) 2019-10-03 2023-11-28 Rom Technologies, Inc. System and method for facilitating cardiac rehabilitation among eligible users
US11515021B2 (en) 2019-10-03 2022-11-29 Rom Technologies, Inc. Method and system to analytically optimize telehealth practice-based billing processes and revenue while enabling regulatory compliance
US20210142893A1 (en) 2019-10-03 2021-05-13 Rom Technologies, Inc. System and method for processing medical claims
US11101028B2 (en) 2019-10-03 2021-08-24 Rom Technologies, Inc. Method and system using artificial intelligence to monitor user characteristics during a telemedicine session
US11317975B2 (en) 2019-10-03 2022-05-03 Rom Technologies, Inc. Method and system for treating patients via telemedicine using sensor data from rehabilitation or exercise equipment
US20210128080A1 (en) 2019-10-03 2021-05-06 Rom Technologies, Inc. Augmented reality placement of goniometer or other sensors
US11075000B2 (en) 2019-10-03 2021-07-27 Rom Technologies, Inc. Method and system for using virtual avatars associated with medical professionals during exercise sessions
US11282608B2 (en) 2019-10-03 2022-03-22 Rom Technologies, Inc. Method and system for using artificial intelligence and machine learning to provide recommendations to a healthcare provider in or near real-time during a telemedicine session
US11325005B2 (en) 2019-10-03 2022-05-10 Rom Technologies, Inc. Systems and methods for using machine learning to control an electromechanical device used for prehabilitation, rehabilitation, and/or exercise
US11915816B2 (en) 2019-10-03 2024-02-27 Rom Technologies, Inc. Systems and methods of using artificial intelligence and machine learning in a telemedical environment to predict user disease states
US11887717B2 (en) 2019-10-03 2024-01-30 Rom Technologies, Inc. System and method for using AI, machine learning and telemedicine to perform pulmonary rehabilitation via an electromechanical machine
US20210134432A1 (en) 2019-10-03 2021-05-06 Rom Technologies, Inc. Method and system for implementing dynamic treatment environments based on patient information
US11282599B2 (en) 2019-10-03 2022-03-22 Rom Technologies, Inc. System and method for use of telemedicine-enabled rehabilitative hardware and for encouragement of rehabilitative compliance through patient-based virtual shared sessions
US11923065B2 (en) 2019-10-03 2024-03-05 Rom Technologies, Inc. Systems and methods for using artificial intelligence and machine learning to detect abnormal heart rhythms of a user performing a treatment plan with an electromechanical machine
US11270795B2 (en) 2019-10-03 2022-03-08 Rom Technologies, Inc. Method and system for enabling physician-smart virtual conference rooms for use in a telehealth context
US20210134425A1 (en) 2019-10-03 2021-05-06 Rom Technologies, Inc. System and method for using artificial intelligence in telemedicine-enabled hardware to optimize rehabilitative routines capable of enabling remote rehabilitative compliance
US20210134412A1 (en) 2019-10-03 2021-05-06 Rom Technologies, Inc. System and method for processing medical claims using biometric signatures
US20210127974A1 (en) 2019-10-03 2021-05-06 Rom Technologies, Inc. Remote examination through augmented reality
US20210134463A1 (en) 2019-10-03 2021-05-06 Rom Technologies, Inc. Systems and methods for remotely-enabled identification of a user infection
US11826613B2 (en) 2019-10-21 2023-11-28 Rom Technologies, Inc. Persuasive motivation for orthopedic treatment
KR102605901B1 (en) * 2020-03-10 2023-11-23 삼성전자주식회사 Apparatus and method for estimating bio-information
CN111528825A (en) * 2020-05-14 2020-08-14 浙江大学 Photoelectric volume pulse wave signal optimization method
JP6916573B1 (en) * 2020-06-01 2021-08-11 株式会社Arblet Information processing systems, servers, information processing methods and programs
WO2021246346A1 (en) * 2020-06-01 2021-12-09 株式会社Arblet Information processing system, server, information processing method, and program
CN111685749B (en) * 2020-06-18 2022-09-02 郑昕 Construction method of pulse pressure wave mathematical model
DE102020124582A1 (en) * 2020-09-22 2022-03-24 Drägerwerk AG & Co. KGaA Medical device for evaluating a pulsatile signal
JP2022080166A (en) * 2020-11-17 2022-05-27 旭化成メディカル株式会社 Heart beat information acquisition device and heart beat information acquisition program
JP2022121340A (en) * 2021-02-08 2022-08-19 阿部 真一 Calculating blood flow rate, blood vessel diameter, blood vessel flow resistance, heart load factor, and the like according to measurement result of blood pressure manometer and displaying them to blood pressure manometer
CN117015338A (en) * 2021-03-18 2023-11-07 泰尔茂株式会社 Arterial pressure estimation device, arterial pressure estimation system, and arterial pressure estimation method
CN113555082B (en) * 2021-07-26 2023-06-16 无锡市第二人民医院 Intelligent guiding training method for respiratory function
WO2023021970A1 (en) * 2021-08-19 2023-02-23 株式会社村田製作所 Biosensor and biological information measuring system
WO2023048158A1 (en) * 2021-09-22 2023-03-30 国立大学法人電気通信大学 Sleep apnea syndrome determination device, sleep apnea syndrome determination method, and program
CN113995396B (en) * 2021-12-24 2022-04-15 北京乾合晶芯电子技术有限公司 Be applied to cardiovascular internal medicine's blood pressure monitor
CN114297186A (en) * 2021-12-30 2022-04-08 广西电网有限责任公司 Power consumption data preprocessing method and system based on deviation coefficient
CN115990001B (en) * 2023-03-21 2024-04-05 首都医科大学宣武医院 Wearable monitoring system, wearable device and storage medium

Family Cites Families (186)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4649929A (en) * 1981-06-11 1987-03-17 Sri International Method and apparatus for diagnosis of coronary artery disease
US4365636A (en) 1981-06-19 1982-12-28 Medicon, Inc. Method of monitoring patient respiration and predicting apnea therefrom
NL9100150A (en) 1991-01-29 1992-08-17 Tno METHOD FOR DETERMINING THE BATTLE VOLUME AND THE HEART MINUTE VOLUME OF THE HUMAN HEART.
US7081095B2 (en) 2001-05-17 2006-07-25 Lynn Lawrence A Centralized hospital monitoring system for automatically detecting upper airway instability and for preventing and aborting adverse drug reactions
JP3219325B2 (en) * 1992-11-05 2001-10-15 日本コーリン株式会社 Respiratory rate measuring device
US5836884A (en) * 1993-12-17 1998-11-17 Pulse Metric, Inc. Method for diagnosing, monitoring and treating hypertension and other cardiac problems
JP3595593B2 (en) * 1995-03-01 2004-12-02 コーリンメディカルテクノロジー株式会社 Blood ejection function evaluation device
JP3583494B2 (en) * 1995-03-01 2004-11-04 コーリンメディカルテクノロジー株式会社 Blood ejection function evaluation device
JPH08317912A (en) 1995-03-23 1996-12-03 Seiko Instr Inc Pulse rate meter
AUPN236595A0 (en) 1995-04-11 1995-05-11 Rescare Limited Monitoring of apneic arousals
US6126595A (en) 1995-05-12 2000-10-03 Seiko Epson Corporation Device for diagnosing physiological state and device for controlling the same
CN1140582A (en) 1995-07-20 1997-01-22 阿兹里尔·佩雷尔 Method of assessing cardiovascular function
JP3794409B2 (en) * 1995-09-13 2006-07-05 セイコーエプソン株式会社 Health condition management device
JP3794410B2 (en) 1995-09-13 2006-07-05 セイコーエプソン株式会社 Health condition management device
EP0818175B1 (en) 1995-11-01 2004-04-28 Seiko Epson Corporation Living body condition measuring apparatus
US5941837A (en) 1995-12-18 1999-08-24 Seiko Epson Corporation Health management device and exercise support device
JPH09220207A (en) 1996-02-19 1997-08-26 Omron Corp Blood pressure calculation device
CN1185985C (en) 1996-03-22 2005-01-26 精工爱普生株式会社 Motion intensity measuring apparatus and momentum measuring apparatus
TW376312B (en) * 1996-04-17 1999-12-11 Seiko Epson Corp Arrhythmia detector
EP1424038B1 (en) 1996-06-12 2006-01-04 Seiko Epson Corporation Device for measuring calorie expenditure
JP3876889B2 (en) 1996-06-12 2007-02-07 セイコーエプソン株式会社 Body temperature measuring device
JP4096376B2 (en) 1996-07-09 2008-06-04 セイコーエプソン株式会社 Relaxation instruction equipment
US5720292A (en) * 1996-07-31 1998-02-24 Medwave, Inc. Beat onset detector
US5772601A (en) 1996-08-26 1998-06-30 Colin Corporation Apparatus for evaluating cardiac function of living subject
EP1057450A3 (en) * 1996-08-28 2001-07-04 Colin Corporation Apparatus for evaluating cardiac function of living subject
DE69728031T2 (en) 1996-09-10 2004-11-11 Seiko Epson Corp. ORGANISM STATUS MEASURING DEVICE AND RELAXATION STATUS INDICATOR
US5865755A (en) 1996-10-11 1999-02-02 Dxtek, Inc. Method and apparatus for non-invasive, cuffless, continuous blood pressure determination
US5980464A (en) 1996-12-19 1999-11-09 Colin Corporation Apparatus for evaluating exercise function of person
JPH10185639A (en) 1996-12-27 1998-07-14 Tokyo Gas Co Ltd Flowmeter
JP3870514B2 (en) 1997-10-31 2007-01-17 セイコーエプソン株式会社 Stroke volume detection device and cardiac function diagnosis device
US5865756A (en) * 1997-06-06 1999-02-02 Southwest Research Institute System and method for identifying and correcting abnormal oscillometric pulse waves
JP3842390B2 (en) * 1997-07-16 2006-11-08 元治 長谷川 Blood pressure measurement device and cardiac function analysis device
US6361501B1 (en) 1997-08-26 2002-03-26 Seiko Epson Corporation Pulse wave diagnosing device
US6334850B1 (en) 1997-11-19 2002-01-01 Seiko Epson Corporation Method of detecting pulse wave, method of detecting artery position, and pulse wave detecting apparatus
US6293915B1 (en) 1997-11-20 2001-09-25 Seiko Epson Corporation Pulse wave examination apparatus, blood pressure monitor, pulse waveform monitor, and pharmacological action monitor
JP3820719B2 (en) 1997-12-24 2006-09-13 セイコーエプソン株式会社 Biological condition measuring device
JP3921775B2 (en) * 1998-01-27 2007-05-30 オムロンヘルスケア株式会社 Blood pressure monitoring device
IL128482A (en) * 1999-02-11 2003-06-24 Ultrasis Internat 1993 Ltd Method and device for continuous analysis of cardiovascular activity of a subject
EP1259157B1 (en) * 2000-03-02 2008-06-11 Itamar Medical Ltd Method and apparatus for the non-invasive detection of particular sleep-state conditions by monitoring the peripheral vascular system
US7806831B2 (en) 2000-03-02 2010-10-05 Itamar Medical Ltd. Method and apparatus for the non-invasive detection of particular sleep-state conditions by monitoring the peripheral vascular system
US6955648B2 (en) 2000-09-29 2005-10-18 New Health Sciences, Inc. Precision brain blood flow assessment remotely in real time using nanotechnology ultrasound
SG94349A1 (en) 2000-10-09 2003-02-18 Healthstats Int Pte Ltd Method and device for monitoring blood pressure
US6918879B2 (en) 2000-10-09 2005-07-19 Healthstats International Pte. Ltd. Method and device for monitoring blood pressure
JP2002224059A (en) * 2001-01-31 2002-08-13 Omron Corp Electronic sphygmomanometer
JP2002224061A (en) * 2001-01-31 2002-08-13 Omron Corp Electronic sphygmomanometer
JP3495344B2 (en) 2001-05-16 2004-02-09 日本コーリン株式会社 Pressure pulse wave detector
JP4759860B2 (en) 2001-07-11 2011-08-31 セイコーエプソン株式会社 Anoxic work threshold detection device
US6773397B2 (en) 2001-10-11 2004-08-10 Draeger Medical Systems, Inc. System for processing signal data representing physiological parameters
US6730038B2 (en) 2002-02-05 2004-05-04 Tensys Medical, Inc. Method and apparatus for non-invasively measuring hemodynamic parameters using parametrics
US6805673B2 (en) 2002-02-22 2004-10-19 Datex-Ohmeda, Inc. Monitoring mayer wave effects based on a photoplethysmographic signal
TW570769B (en) 2002-04-26 2004-01-11 Chin-Yu Lin Method and device for measuring pulse signals for simultaneously obtaining pulse pressure and blood flow rate
US6869402B2 (en) 2002-08-27 2005-03-22 Precision Pulsus, Inc. Method and apparatus for measuring pulsus paradoxus
DE10243265A1 (en) * 2002-09-17 2004-03-25 Andreas Nuske Heart condition diagnosis method is based on analysis of bioelectrical signals recorded using a measurement glove that has a pulse sensor and electronics with an evaluation algorithm stored in ROM
US8672852B2 (en) * 2002-12-13 2014-03-18 Intercure Ltd. Apparatus and method for beneficial modification of biorhythmic activity
US20050096557A1 (en) 2003-01-08 2005-05-05 Frederick Vosburgh Noninvasive cardiovascular monitoring methods and devices
JP4025220B2 (en) 2003-03-03 2007-12-19 ▲苅▼尾 七臣 Blood pressure monitor and cardiovascular disease risk analysis program
US7524292B2 (en) 2003-04-21 2009-04-28 Medtronic, Inc. Method and apparatus for detecting respiratory disturbances
JP4327524B2 (en) * 2003-07-03 2009-09-09 ▲苅▼尾 七臣 Blood pressure abnormality inspection device at load change
US7244225B2 (en) 2003-10-07 2007-07-17 Cardiomedics, Inc. Devices and methods for non-invasively improving blood circulation
WO2005069740A2 (en) * 2004-01-27 2005-08-04 Cardiometer Ltd. Method and system for cardiovascular system diagnosis
JP2005237472A (en) 2004-02-24 2005-09-08 七臣 ▲苅▼尾 Sphygmomanometry instrument
JP3987053B2 (en) 2004-03-30 2007-10-03 株式会社東芝 Sleep state determination device and sleep state determination method
US7828711B2 (en) 2004-08-16 2010-11-09 Cardiac Pacemakers, Inc. Method and apparatus for modulating cellular growth and regeneration using ventricular assist device
US20060047202A1 (en) 2004-09-02 2006-03-02 Elliott Stephen B Method and system of breathing therapy for reducing sympathetic predominance with consequent positive modification of hypertension
CN1284512C (en) * 2004-10-21 2006-11-15 中国人民解放军空军航空医学研究所 Digital medical information monitoring and control system for full ward
JP4752259B2 (en) * 2004-12-10 2011-08-17 オムロンヘルスケア株式会社 Electronic blood pressure monitor and blood pressure measurement system
WO2006079829A1 (en) * 2005-01-27 2006-08-03 Uws Ventures Limited Phosphoglycerides for use in improving heart rate recovery and increasing exercise capacity
JP4342455B2 (en) 2005-02-03 2009-10-14 株式会社東芝 Health management device and health management system
US20060195035A1 (en) * 2005-02-28 2006-08-31 Dehchuan Sun Non-invasive radial artery blood pressure waveform measuring apparatus system and uses thereof
CA2602899A1 (en) 2005-03-21 2006-09-28 Software Solutions Limited System for continuous blood pressure monitoring
US8423108B2 (en) 2005-03-24 2013-04-16 Intelomed, Inc. Device and system that identifies cardiovascular insufficiency
DE102005014950A1 (en) * 2005-04-01 2006-10-12 Braun Gmbh Method for determining cardiovascular parameters and device and computer program product for carrying out the method
JP5687741B2 (en) 2005-04-22 2015-03-18 フクダ電子株式会社 Biological information output device and method, and biological information report
WO2006121455A1 (en) * 2005-05-10 2006-11-16 The Salk Institute For Biological Studies Dynamic signal processing
CN1723839A (en) * 2005-07-21 2006-01-25 高春平 Method and device for testing health-index of individualized and three-D type
CN1903117A (en) * 2005-07-27 2007-01-31 孙德铨 Non penetration type system for measuring radial artery blood pressure wave and its application
WO2007049174A1 (en) * 2005-10-24 2007-05-03 Philips Intellectual Property & Standards Gmbh System and method for determining the blood pressure of a patient
JP2007117591A (en) 2005-10-31 2007-05-17 Konica Minolta Sensing Inc Pulse wave analyzer
EP1785088A1 (en) * 2005-11-14 2007-05-16 Congener Wellness Corp. A system and method for the management and control of cardiovascular related diseases, such as hypertension
CN1985750B (en) * 2005-12-21 2011-03-23 深圳迈瑞生物医疗电子股份有限公司 Pulse wave detecting method and device by means of cardiac symbol signal
JP2007190275A (en) 2006-01-20 2007-08-02 Omron Healthcare Co Ltd Respiration training device
US7607243B2 (en) * 2006-05-03 2009-10-27 Nike, Inc. Athletic or other performance sensing systems
JP4901309B2 (en) 2006-05-31 2012-03-21 株式会社デンソー Biological state detection device, control device, and pulse wave sensor mounting device
JP2008005964A (en) 2006-06-28 2008-01-17 Omron Healthcare Co Ltd Apnea controller and program for apnea control
JP2008061824A (en) 2006-09-07 2008-03-21 Omron Healthcare Co Ltd Medical measuring instrument, biosignal waveform extraction method and biosignal waveform extraction program
US20080064965A1 (en) * 2006-09-08 2008-03-13 Jay Gregory D Devices and methods for measuring pulsus paradoxus
CN100466968C (en) 2006-09-29 2009-03-11 北京新兴阳升科技有限公司 Detection method with blood pressure monitor and korotkoff sound delaying and pulse wave conducting time signal generator
JP4789203B2 (en) * 2006-10-02 2011-10-12 フクダ電子株式会社 Blood pressure reflex function measuring device
US8652040B2 (en) 2006-12-19 2014-02-18 Valencell, Inc. Telemetric apparatus for health and environmental monitoring
US9044136B2 (en) 2007-02-16 2015-06-02 Cim Technology Inc. Wearable mini-size intelligent healthcare system
US8047998B2 (en) 2007-04-17 2011-11-01 General Electric Company Non-invasive blood pressure determination method
DE102007020038A1 (en) 2007-04-27 2008-10-30 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Evidence of apnea with blood pressure dependent detected signals
US20080319327A1 (en) * 2007-06-25 2008-12-25 Triage Wireless, Inc. Body-worn sensor featuring a low-power processor and multi-sensor array for measuring blood pressure
JP4714194B2 (en) * 2007-08-09 2011-06-29 オムロンヘルスケア株式会社 Blood pressure measurement device
US20090124914A1 (en) 2007-11-08 2009-05-14 Kuo Terry B J Analysis system and a method for pulse diagnosis in chinese medicine
US20090156946A1 (en) 2007-12-13 2009-06-18 Welch Allyn, Inc. Blood pressure motion sensing
JP5045514B2 (en) 2008-03-19 2012-10-10 オムロンヘルスケア株式会社 Electronic blood pressure monitor
JP5151690B2 (en) 2008-05-27 2013-02-27 オムロンヘルスケア株式会社 Blood pressure information measuring device and index acquisition method
JP5211910B2 (en) 2008-07-23 2013-06-12 オムロンヘルスケア株式会社 Biological information management system and measuring instrument
JP5336803B2 (en) 2008-09-26 2013-11-06 株式会社東芝 Pulse wave measuring device
JP5185785B2 (en) * 2008-11-19 2013-04-17 オムロンヘルスケア株式会社 Health condition judgment device
EP2189111A1 (en) 2008-11-21 2010-05-26 Pulsion Medical Systems AG Apparatus and method for determining a physiologic parameter
CN101773387B (en) 2009-01-08 2011-12-14 香港中文大学 Body feeling network-based sleeveless driven pulse pressure measurement and automatic calibration device
JP2010200901A (en) 2009-03-02 2010-09-16 Nippon Koden Corp Biological signal measuring apparatus
JP5209545B2 (en) * 2009-03-09 2013-06-12 株式会社デンソー Biopsy device, program, and recording medium
US20100268097A1 (en) 2009-03-20 2010-10-21 Edwards Lifesciences Corporation Monitoring Peripheral Decoupling
US8057400B2 (en) * 2009-05-12 2011-11-15 Angiologix, Inc. System and method of measuring changes in arterial volume of a limb segment
KR101640498B1 (en) 2009-05-22 2016-07-19 삼성전자주식회사 Blood pressure estimating apparatus and method by using variable characteristic ratio
CN201409913Y (en) 2009-06-10 2010-02-24 吕景文 Individual physical index monitoring system
JP5679971B2 (en) 2009-08-13 2015-03-04 英次 麻野井 Respiratory waveform information computing device and medical device using respiratory waveform information
CN102043893A (en) 2009-10-13 2011-05-04 北京大学 Disease pre-warning method and system
JP5536582B2 (en) 2009-10-22 2014-07-02 日本光電工業株式会社 Biological parameter display device
JP5850861B2 (en) 2010-01-29 2016-02-03 エドワーズ ライフサイエンシーズ コーポレイションEdwards Lifesciences Corporation Eliminating the effects of irregular cardiac cycles in determining cardiovascular parameters
US8668649B2 (en) * 2010-02-04 2014-03-11 Siemens Medical Solutions Usa, Inc. System for cardiac status determination
EP2364640A1 (en) 2010-03-11 2011-09-14 BIOTRONIK SE & Co. KG Monitoring device and method for operating a monitoring device
JP5504477B2 (en) * 2010-03-16 2014-05-28 国立大学法人富山大学 Fingertip pulse wave analyzer and vascular endothelial function evaluation system using the same
US8834378B2 (en) 2010-07-30 2014-09-16 Nellcor Puritan Bennett Ireland Systems and methods for determining respiratory effort
US8315812B2 (en) 2010-08-12 2012-11-20 Heartflow, Inc. Method and system for patient-specific modeling of blood flow
EP2668896B1 (en) * 2011-01-24 2014-12-17 Act Medical Service Co., Ltd. Blood vessel pulse-wave measuring system
JP5605269B2 (en) * 2011-02-28 2014-10-15 セイコーエプソン株式会社 Beat detector
JP5623955B2 (en) 2011-03-29 2014-11-12 シチズンホールディングス株式会社 Sphygmomanometer
EP2524647A1 (en) * 2011-05-18 2012-11-21 Alain Gilles Muzet System and method for determining sleep stages of a person
JP5738673B2 (en) 2011-05-24 2015-06-24 オムロンヘルスケア株式会社 Blood pressure measurement device
AU2012284039B2 (en) * 2011-07-18 2017-03-30 Critical Care Diagnostics, Inc. Methods of treating cardiovascular diseases and predicting the efficacy of exercise therapy
JP2013031568A (en) * 2011-08-02 2013-02-14 Tdk Corp Method and apparatus for monitoring respiration, and sphygmomanometer with respiration monitoring function
CN103781414B (en) 2011-09-16 2016-08-24 皇家飞利浦有限公司 For estimating equipment and the method for the heart rate during motion
US20130085079A1 (en) * 2011-09-30 2013-04-04 Somalogic, Inc. Cardiovascular Risk Event Prediction and Uses Thereof
JP5927843B2 (en) * 2011-10-28 2016-06-01 セイコーエプソン株式会社 Congestion determination device, pulse wave measurement device, and congestion determination method
US9049995B2 (en) 2012-01-12 2015-06-09 Pacesetter, Inc. System and method for detecting pulmonary congestion based on stroke volume using an implantable medical device
WO2013113055A1 (en) * 2012-01-30 2013-08-08 Campbell Duncan Islay Method and apparatus for non-invasive determination of cardiac output
JP5953878B2 (en) * 2012-03-30 2016-07-20 富士通株式会社 State change detection method, program, and apparatus
US10405791B2 (en) 2013-03-15 2019-09-10 Yingchang Yang Method and continuously wearable noninvasive apparatus for automatically detecting a stroke and other abnormal health conditions
CN102697506B (en) 2012-05-29 2014-11-26 广州乾华生物科技有限公司 Method and system for monitoring action response condition
JP5984088B2 (en) * 2012-06-15 2016-09-06 国立大学法人 東京大学 Noninvasive continuous blood pressure monitoring method and apparatus
JP2014014556A (en) * 2012-07-10 2014-01-30 Omron Healthcare Co Ltd Electronic sphygmomanometer and sphygmomanometry method
JP6019854B2 (en) 2012-07-13 2016-11-02 セイコーエプソン株式会社 Blood pressure measuring device and parameter correction method for central blood pressure estimation
JP2015013635A (en) * 2012-12-27 2015-01-22 株式会社東海理化電機製作所 Tire position determination system
EP2759257B1 (en) * 2013-01-25 2016-09-14 UP-MED GmbH Method, logic unit and system for determining a parameter representative for the patient's volume responsiveness
JP2014171589A (en) 2013-03-07 2014-09-22 Seiko Epson Corp Atrial fibrillation analyzation equipment and program
US9949696B2 (en) 2013-03-14 2018-04-24 Tensys Medical, Inc. Apparatus and methods for computing cardiac output of a living subject via applanation tonometry
US9345436B2 (en) 2013-03-14 2016-05-24 HighDim GmbH Apparatus and methods for computing cardiac output of a living subject
CN103126655B (en) 2013-03-14 2014-10-08 浙江大学 Non-binding goal non-contact pulse wave acquisition system and sampling method
CN103230268B (en) * 2013-03-22 2016-02-03 浙江理工大学 A kind of human body detection device that can carry out remote monitoring
US10390761B2 (en) 2013-04-16 2019-08-27 Kyocera Corporation Device, device control method and control program, and system
CN104138253B (en) 2013-05-11 2016-06-15 吴健康 A kind of noinvasive arteriotony method for continuous measuring and equipment
CN103230267B (en) 2013-05-14 2015-06-03 北京理工大学 Anti-movement-interference extraction method for pulse rates
US9314211B2 (en) 2013-07-31 2016-04-19 Omron Healthcare Co., Ltd. Blood pressure measurement device having function of determining rest condition of patient
CN103479343B (en) * 2013-09-27 2015-02-25 上海交通大学 Central aortic pressure detection system and method based on oscillating sphygmomanometer signals
JP6347097B2 (en) 2013-10-07 2018-06-27 セイコーエプソン株式会社 Portable device and heartbeat arrival time measurement control method
KR20160075677A (en) * 2013-10-23 2016-06-29 콴투스, 아이엔씨. Consumer biometric devices
US20150164351A1 (en) 2013-10-23 2015-06-18 Quanttus, Inc. Calculating pulse transit time from chest vibrations
JP5911840B2 (en) * 2013-11-25 2016-04-27 株式会社カオテック研究所 Diagnostic data generation device and diagnostic device
CN104055496B (en) * 2014-01-15 2016-04-20 中国航天员科研训练中心 A kind of method of estimation of the sports load level based on heart source property signal
US20150196209A1 (en) 2014-01-15 2015-07-16 Microsoft Corporation Cardiovascular risk factor sensing device
CN103892811B (en) * 2014-01-22 2016-09-07 杭州优体科技有限公司 A kind of ambulatory blood pressure joint-detection and the system of analysis
CN104808776A (en) * 2014-01-24 2015-07-29 北京奇虎科技有限公司 Device and method for detecting continuous attaching of head-wearing intelligent device on human body
JP6282887B2 (en) 2014-02-28 2018-02-21 国立大学法人広島大学 Blood pressure measuring device and blood pressure measuring method
US10610113B2 (en) 2014-03-31 2020-04-07 The Regents Of The University Of Michigan Miniature piezoelectric cardiovascular monitoring system
WO2015162566A1 (en) * 2014-04-24 2015-10-29 Ecole Polytechnique Federale De Lausanne (Epfl) A method and a device for non invasive blood pressure measurement
WO2015178439A2 (en) * 2014-05-20 2015-11-26 株式会社Ainy Device and method for supporting diagnosis of central/obstructive sleep apnea, and computer-readable medium having stored thereon program for supporting diagnosis of central/obstructive sleep apnea
JP6358865B2 (en) 2014-06-13 2018-07-18 株式会社デンソー Sphygmomanometer
CN104091080B (en) * 2014-07-14 2017-02-22 中国科学院合肥物质科学研究院 Intelligent bodybuilding guidance system and closed-loop guidance method thereof
WO2016017579A1 (en) 2014-07-28 2016-02-04 シナノケンシ株式会社 Biological information reading device
US10939848B2 (en) 2014-07-28 2021-03-09 S & V Siu Associates, Llc Method and apparatus for assessing respiratory distress
CN105455797B (en) * 2014-08-19 2020-01-07 南京茂森电子技术有限公司 Autonomic nerve heart regulation function measuring method and device
US20170251927A1 (en) * 2014-08-27 2017-09-07 Nec Corporation Blood pressure determination device, blood pressure determination method, recording medium for recording blood pressure determination program, and blood pressure measurement device
CN104188639B (en) * 2014-09-10 2017-02-15 朱宇东 Ambulatory blood pressure continuous monitoring and real-time analysis system
JP6280487B2 (en) 2014-10-16 2018-02-14 東京エレクトロン株式会社 Substrate processing method and substrate processing apparatus
JP6366463B2 (en) 2014-10-31 2018-08-01 オムロンヘルスケア株式会社 Blood pressure measurement device
CN104352228A (en) 2014-11-10 2015-02-18 小米科技有限责任公司 Method and device for processing application program
CN104382569B (en) 2014-12-08 2017-04-12 天津工业大学 Fiber-optic sensing intelligent garment and heart sound parameter processing methods thereof
CN104665821A (en) * 2015-01-26 2015-06-03 周常安 Cardiovascular health monitoring device and cardiovascular health monitoring method
CN104665799A (en) * 2015-01-26 2015-06-03 周常安 Blood pressure managing device and blood pressure managing method
JP3214887U (en) 2015-01-26 2018-02-15 周常安CHOU, Chang−An Cardiovascular health monitoring device
CN204618202U (en) * 2015-03-11 2015-09-09 佛山职业技术学院 A kind of intelligent bangle of athlete's status data remote capture
CN204708829U (en) 2015-04-24 2015-10-21 吉林大学 A kind of wireless breathing, pulse monitoring device
CN104856661A (en) 2015-05-11 2015-08-26 北京航空航天大学 Wearable continuous blood pressure estimating system and method based on dynamic compensation of diastolic blood pressure
CN105030195A (en) * 2015-06-02 2015-11-11 牛欣 Three-position and nine-indicator multi-information acquisition and recognition device based on finger feel pressure application and microarray sensing
CN104958064A (en) * 2015-07-15 2015-10-07 四川宇峰科技发展有限公司 Wearable arteriosclerosis detector and pulse wave velocity detecting method
CN105054918B (en) 2015-07-28 2018-05-22 杭州暖芯迦电子科技有限公司 A kind of blood pressure computational methods and blood pressure instrument based on the pulse reflective wave transmission time
CN105078474A (en) * 2015-08-21 2015-11-25 武汉苏酷科技有限公司 Blood glucose and blood pressure monitoring and control system
CN204909471U (en) * 2015-09-05 2015-12-30 于清 Acquisition and analysis processing apparatus of sports psychology index data
CN105266828A (en) * 2015-09-05 2016-01-27 于清 Sports psychology index data acquisition analysis and processing device
CN105361858B (en) * 2015-12-10 2018-04-03 广东小天才科技有限公司 A kind of method and wearable device of blood pressure data processing
JP6631376B2 (en) 2016-04-15 2020-01-15 オムロンヘルスケア株式会社 Pulse wave detecting device, biological information measuring device, control method of pulse wave detecting device, and control program of pulse wave detecting device
US11076813B2 (en) 2016-07-22 2021-08-03 Edwards Lifesciences Corporation Mean arterial pressure (MAP) derived prediction of future hypotension

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11882755B2 (en) 2019-04-12 2024-01-23 Semiconductor Energy Laboratory Co., Ltd. Display device and system

Also Published As

Publication number Publication date
JP6679006B2 (en) 2020-04-15
CN108882871B (en) 2021-04-16
EP3427653B1 (en) 2021-03-31
CN108882877B (en) 2023-11-03
CN108882867B (en) 2021-12-07
JPWO2017179703A1 (en) 2019-02-28
US20190150755A1 (en) 2019-05-23
WO2017179697A1 (en) 2017-10-19
JPWO2017179694A1 (en) 2019-02-21
EP3427655A4 (en) 2019-12-04
EP3427650B1 (en) 2021-06-23
EP3430989A1 (en) 2019-01-23
US20190175027A1 (en) 2019-06-13
JP6835395B2 (en) 2021-02-24
WO2017179694A1 (en) 2017-10-19
JPWO2017179701A1 (en) 2019-02-21
EP3427652A1 (en) 2019-01-16
JP6721156B2 (en) 2020-07-08
US20190110700A1 (en) 2019-04-18
JPWO2017179700A1 (en) 2019-02-21
CN108882868A (en) 2018-11-23
US20190090818A1 (en) 2019-03-28
JPWO2017179693A1 (en) 2019-02-21
CN108882870A (en) 2018-11-23
EP3427649A1 (en) 2019-01-16
WO2017179698A1 (en) 2017-10-19
EP3427650A4 (en) 2019-12-11
EP3440995A4 (en) 2020-02-19
WO2017179695A1 (en) 2017-10-19
US20190159685A1 (en) 2019-05-30
EP3427655B1 (en) 2021-03-10
CN108882873A (en) 2018-11-23
JP6721154B2 (en) 2020-07-08
JP6659830B2 (en) 2020-03-04
US11363961B2 (en) 2022-06-21
JPWO2017179696A1 (en) 2019-02-21
EP3427654A1 (en) 2019-01-16
JP6679005B2 (en) 2020-04-15
EP3440995A1 (en) 2019-02-13
US20190117095A1 (en) 2019-04-25
CN109069035A (en) 2018-12-21
JP6659831B2 (en) 2020-03-04
EP3427650A1 (en) 2019-01-16
EP3427651A1 (en) 2019-01-16
CN108882873B (en) 2021-08-06
EP3427656A1 (en) 2019-01-16
WO2017179693A1 (en) 2017-10-19
EP3427648A1 (en) 2019-01-16
EP3430989B1 (en) 2021-06-09
CN108882872A (en) 2018-11-23
CN109069013A (en) 2018-12-21
EP3427655A1 (en) 2019-01-16
CN108882869A (en) 2018-11-23
EP3427649A4 (en) 2019-10-30
JP6721155B2 (en) 2020-07-08
US11617516B2 (en) 2023-04-04
JPWO2017179699A1 (en) 2019-02-21
EP3427653A4 (en) 2019-12-11
US20190159723A1 (en) 2019-05-30
EP3427648A4 (en) 2019-11-27
EP3427651A4 (en) 2019-12-11
JPWO2017179698A1 (en) 2019-02-21
EP3427656A4 (en) 2019-12-11
WO2017179702A1 (en) 2017-10-19
CN108882878B (en) 2021-04-23
JP6721153B2 (en) 2020-07-08
CN108882869B (en) 2021-03-23
EP3427654A4 (en) 2019-12-11
CN108882867A (en) 2018-11-23
EP3427656B1 (en) 2023-03-29
EP3440995B1 (en) 2021-06-16
EP3427649B1 (en) 2021-03-10
EP3427652A4 (en) 2019-12-04
CN109069035B (en) 2021-09-28
EP3427652B1 (en) 2021-06-09
CN108882870B (en) 2021-08-13
WO2017179699A1 (en) 2017-10-19
JPWO2017179697A1 (en) 2019-02-21
JPWO2017179695A1 (en) 2019-02-21
JP6687263B2 (en) 2020-04-22
WO2017179696A1 (en) 2017-10-19
CN109069013B (en) 2021-09-14
US20190159722A1 (en) 2019-05-30
CN108882878A (en) 2018-11-23
WO2017179701A1 (en) 2017-10-19
JP6679051B2 (en) 2020-04-15
US20190159682A1 (en) 2019-05-30
CN108882868B (en) 2021-05-18
US11246501B2 (en) 2022-02-15
US20190125252A1 (en) 2019-05-02
US20190117084A1 (en) 2019-04-25
CN108882877A (en) 2018-11-23
JPWO2017179702A1 (en) 2019-02-21
WO2017179703A1 (en) 2017-10-19
CN108882871A (en) 2018-11-23
EP3430989A4 (en) 2019-10-30
WO2017179700A1 (en) 2017-10-19
CN108882872B (en) 2021-07-20

Similar Documents

Publication Publication Date Title
EP3427653B1 (en) Biological information analysis device, system, and program
WO2016018906A1 (en) Method and apparatus for assessing respiratory distress

Legal Events

Date Code Title Description
STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE

PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20181008

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

AX Request for extension of the european patent

Extension state: BA ME

DAV Request for validation of the european patent (deleted)
DAX Request for extension of the european patent (deleted)
A4 Supplementary search report drawn up and despatched

Effective date: 20191107

RIC1 Information provided on ipc code assigned before grant

Ipc: A61B 5/11 20060101ALN20191101BHEP

Ipc: A61B 5/08 20060101ALN20191101BHEP

Ipc: A61B 5/145 20060101ALN20191101BHEP

Ipc: A61B 5/022 20060101ALN20191101BHEP

Ipc: A61B 5/021 20060101AFI20191101BHEP

Ipc: A61B 5/00 20060101ALN20191101BHEP

REG Reference to a national code

Ref country code: DE

Ref legal event code: R079

Ref document number: 602017035793

Country of ref document: DE

Free format text: PREVIOUS MAIN CLASS: A61B0005020000

Ipc: A61B0005021000

GRAP Despatch of communication of intention to grant a patent

Free format text: ORIGINAL CODE: EPIDOSNIGR1

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: GRANT OF PATENT IS INTENDED

RIC1 Information provided on ipc code assigned before grant

Ipc: A61B 5/11 20060101ALN20200901BHEP

Ipc: A61B 5/08 20060101ALN20200901BHEP

Ipc: A61B 5/022 20060101ALN20200901BHEP

Ipc: A61B 5/021 20060101AFI20200901BHEP

Ipc: A61B 5/145 20060101ALN20200901BHEP

Ipc: A61B 5/00 20060101ALN20200901BHEP

RIC1 Information provided on ipc code assigned before grant

Ipc: A61B 5/11 20060101ALN20200904BHEP

Ipc: A61B 5/08 20060101ALN20200904BHEP

Ipc: A61B 5/145 20060101ALN20200904BHEP

Ipc: A61B 5/021 20060101AFI20200904BHEP

Ipc: A61B 5/022 20060101ALN20200904BHEP

Ipc: A61B 5/00 20060101ALN20200904BHEP

INTG Intention to grant announced

Effective date: 20200924

GRAS Grant fee paid

Free format text: ORIGINAL CODE: EPIDOSNIGR3

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: GRANT OF PATENT IS INTENDED

GRAA (expected) grant

Free format text: ORIGINAL CODE: 0009210

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE PATENT HAS BEEN GRANTED

AK Designated contracting states

Kind code of ref document: B1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

REG Reference to a national code

Ref country code: GB

Ref legal event code: FG4D

Ref country code: CH

Ref legal event code: EP

RIN1 Information on inventor provided before grant (corrected)

Inventor name: SATO, HIRONORI

Inventor name: TSUTSUMI, MASAKAZU

Inventor name: OBAYASHI, KEIICHI

Inventor name: MIYAGAWA, KEN

Inventor name: WADA, HIROTAKA

Inventor name: KASAI, MASAAKI

Inventor name: UENOYAMA, TORU

Inventor name: OTA, YUYA

Inventor name: TSUCHIYA, NAOKI

Inventor name: NAKAJIMA, HIROSHI

Inventor name: KOKUBO, AYAKO

Inventor name: SHIGA, TOSHIKAZU

Inventor name: KAN, ERIKO

Inventor name: KUWABARA, MITSUO

RAP3 Party data changed (applicant data changed or rights of an application transferred)

Owner name: OMRON CORPORATION

Owner name: OMRON HEALTHCARE CO., LTD.

REG Reference to a national code

Ref country code: AT

Ref legal event code: REF

Ref document number: 1376010

Country of ref document: AT

Kind code of ref document: T

Effective date: 20210415

REG Reference to a national code

Ref country code: DE

Ref legal event code: R096

Ref document number: 602017035793

Country of ref document: DE

REG Reference to a national code

Ref country code: IE

Ref legal event code: FG4D

REG Reference to a national code

Ref country code: LT

Ref legal event code: MG9D

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: BG

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210630

Ref country code: NO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210630

Ref country code: HR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: FI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: LV

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

REG Reference to a national code

Ref country code: NL

Ref legal event code: MP

Effective date: 20210331

REG Reference to a national code

Ref country code: AT

Ref legal event code: MK05

Ref document number: 1376010

Country of ref document: AT

Kind code of ref document: T

Effective date: 20210331

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: EE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: CZ

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: LT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: NL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: SM

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: AT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210731

Ref country code: PL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: PT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210802

Ref country code: SK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: RO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: LU

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210414

REG Reference to a national code

Ref country code: DE

Ref legal event code: R097

Ref document number: 602017035793

Country of ref document: DE

REG Reference to a national code

Ref country code: BE

Ref legal event code: MM

Effective date: 20210430

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: LI

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210430

Ref country code: MC

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: CH

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210430

Ref country code: DK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: AL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: ES

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

PLBE No opposition filed within time limit

Free format text: ORIGINAL CODE: 0009261

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT

GBPC Gb: european patent ceased through non-payment of renewal fee

Effective date: 20210630

26N No opposition filed

Effective date: 20220104

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210414

Ref country code: GB

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210630

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210731

Ref country code: FR

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210531

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

Ref country code: BE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210430

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: RS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

P01 Opt-out of the competence of the unified patent court (upc) registered

Effective date: 20230512

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: CY

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: HU

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT; INVALID AB INITIO

Effective date: 20170414

Ref country code: GR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20210331

PGFP Annual fee paid to national office [announced via postgrant information from national office to epo]

Ref country code: DE

Payment date: 20230228

Year of fee payment: 7